Hire TypeScript Developers in India
Before you hire TypeScript developers in India, one honest thing needs saying: nobody is only a TypeScript developer. The language sits on top of a runtime and a framework, so what you are actually hiring is a frontend, backend or full stack engineer whose codebase happens to be typed. The thing worth screening for is narrower and far more useful. Do they use the type system to delete whole categories of bug, or do they fight it and reach for any? You can see the answer in an hour.
Nobody Is Only a TypeScript Developer, and Your Brief Should Say So
Compare it to a brief for a Go developer or an iOS developer. Those name a runtime and an ecosystem, and the job is reasonably well defined by the name. TypeScript names neither. It is a checker that runs before your code does, and then gets out of the way entirely. A candidate who has spent four years in React with a typed component library and a candidate who has spent four years in a typed Node service share a syntax and almost nothing else about what they do all day. Hiring against the language alone is how teams end up with someone technically qualified and practically useless for the work in front of them.
A language layer, not a job description
Strip the types out of any TypeScript file and you have JavaScript that runs identically. That is the design goal, and it tells you where the skill lives. The type system does not change what your program does. It changes what your team can change safely, how quickly a refactor is proved wrong, and how much of an unfamiliar file a new engineer can trust without reading its callers. Those are real benefits and they are worth money. They are also entirely orthogonal to whether the person can build the thing you need built.
What the search term usually means in practice
When a client writes to us about TypeScript engineers, roughly three intentions sit behind it. Some have a JavaScript codebase that has outgrown itself and want it migrated by someone who has done it before. Some have a typed codebase already and want a contributor who will not make it worse. A third group is using the word as shorthand for modern web work, and what they actually want is a React or Node engineer who is not going to hand back untyped code. All three are legitimate. They lead to different screening and different people.
The part that is genuinely TypeScript specific
There is a real skill here, and it is not knowledge of syntax. It is judgement about how much modelling a problem deserves, where to put the guarantee, and when a clever type is costing more in reading time than it saves in bugs. Add to that the operational side: compiler configuration, build wiring, declaration files for dependencies that ship none, and keeping a large project checking fast enough that people do not disable the check. That list is short, teachable, and still separates senior from mid level reliably.
Why this page ends by pointing you elsewhere
We could pretend otherwise and it would probably convert better. But the useful version of this page tells you what to test for, gives you the questions that expose the difference in an hour, and then sends you to the framework page that matches the actual job. If your codebase is a Next.js app, the hire is a Next.js engineer with strong typing habits. If it is a queue worker, the hire is a Node engineer with the same habits. The links are at the bottom and they are the point of the page.
What Does a Codebase Full of any Actually Cost You?
This is the single most useful signal available to a non specialist interviewer, and it survives contact with reality better than any whiteboard exercise. The keyword any switches the checker off for a value and everything that value touches. It is occasionally correct. It is far more often a developer under deadline pressure making a compiler error disappear without understanding it. Counting how often that happened in a candidate's last project, and asking what they did about it, tells you more about seniority than a decade of listed experience.
Implicit any is a settings problem, explicit any is a judgement problem
These are two different failures and they need separating during a review. Implicit any appears when a parameter has no annotation and the compiler cannot infer one, and it happens by default unless noImplicitAny is enabled. That is a configuration decision somebody made once, probably years ago, and it can be fixed centrally. Explicit any is someone typing the word. That is a choice made at a keyboard, in a file, under pressure. When you audit a codebase, count them separately, because the remedies have nothing in common.
How the damage spreads
The cost is not the one value. Assign an any to a variable and that variable is now unchecked. Pass it into a function and the checks inside that function still run, but every guarantee you thought you had about what arrives is gone. Spread it into an object and the object's shape stops being enforced. A single any at a data boundary can quietly disable checking across an entire feature, and nothing in the editor will tell you, because from the compiler's point of view you asked for exactly this.
unknown is the honest version
When you genuinely do not know a value's shape, and at a network boundary you genuinely do not, unknown says so without surrendering. It accepts anything on the way in, like any, but refuses every operation on the way out until you narrow it. You cannot read a property, call it, or pass it somewhere typed. That friction is the entire feature. A candidate who reaches for unknown at boundaries and any nowhere has internalised the difference between describing data and trusting it, which is most of what this job is.
Measuring it before you argue about it
Arguments about code quality go better with a number attached. Type coverage tooling will report the share of expressions in a project with a known type, and running it once gives you a baseline that is hard to dispute. Grep for suppression comments as well, since those hide errors the compiler did find. Neither figure is a grade. What matters is the direction: a project where the number improves every quarter is being maintained, and one where it slides has a schedule problem that typing will not fix.
Strictness Settings and What Switching Them On Reveals
Ask a candidate what is in the compiler configuration of the project they just left. It is a boring question and it works, because the answer separates people who inherited a setup from people who have argued about one. Strict mode is not a single behaviour. It is a family of flags, each disabling a specific piece of unsound permissiveness that the language kept for compatibility with the JavaScript it grew out of. Which ones a team has turned on, and which ones they turned back off after a week, is a compressed history of how much they actually trust their own types.
strictNullChecks is the flag that matters
With it off, null and undefined are assignable to almost every type, which means a string might not be a string and the compiler will not mention it. Switching it on is what converts the most common runtime crash in the ecosystem into a build error. It is also the flag that produces the largest wave of errors on an old project, because it surfaces every optional value the team has been handling by hope. Work through that wave and the payoff is immediate. Skip it and you have autocomplete with a safety story attached.
noUncheckedIndexedAccess and the lookup nobody checks
Reading the fifth element of an array gives you the element type by default, even when the array holds three things. The same applies to reading a key out of a record. This flag adds undefined to the result of every index access, which is what actually happens at runtime, and the effect on a data heavy codebase is uncomfortable and instructive. It is not in the strict family for good reason. Teams that have enabled it deliberately, and can explain where they carved out exceptions, tend to be teams that have debugged the alternative.
The flags people quietly turn back off
exactOptionalPropertyTypes distinguishes a missing property from one explicitly set to undefined, which sounds pedantic until a partial update overwrites a field with nothing. useUnknownInCatchVariables stops a caught error being treated as anything you like. Both get switched off during migrations and never revisited. Neither decision is wrong on its own. What you want from a candidate is that the decision was made with a reason and written down somewhere, rather than discovered later by whoever inherits the repository.
A ratchet, not a switch
The migration that works is boring. Enable one flag, fix what it reports, merge, repeat. Keep each step inside a sprint so it never competes with feature work for a whole quarter. Where a file is genuinely not worth converting yet, exclude it explicitly rather than weakening the setting for everyone. The failure pattern is easy to recognise: someone turns on the full strict family on a Friday, opens a branch with several thousand errors, and that branch is still open in March.
Narrowing and Discriminated Unions Are the Everyday Tools
Most of the value in a typed codebase comes from a handful of techniques used constantly, not from anything exotic. Modelling the states a thing can be in, then letting the checker prove that every state is handled, is the whole game for application code. Candidates who work this way write code where impossible combinations cannot be constructed. Candidates who do not write interfaces with six optional fields and comments explaining which four are set together, which is a documentation problem pretending to be a type.
Control flow narrowing does most of the work
Check a value against null and inside that branch the checker knows it is not null. Use typeof on a union of string and number and each branch has one type. This analysis follows early returns, ternaries, switch statements and logical operators, and once someone is used to it they stop writing defensive checks the compiler has already proved unnecessary. The tell for inexperience is casting immediately after a check that already narrowed the value, which means the person does not trust the tool they are using.
Discriminated unions instead of optional field soup
A request is loading, or it succeeded with data, or it failed with an error. Modelled as one object with optional data and optional error fields, every consumer has to guess which combination is real, and one of them will guess wrong. Modelled as a union of three shapes with a shared literal tag, the invalid combinations cannot be written down. This single pattern removes more defensive branching from a React or Node codebase than anything else in the language, and it is the first thing we look for in a candidate's sample code.
Exhaustiveness checking with never
Once states are a union, a switch over the tag can be made to fail at build time if a case is missing. Assign the value to a never typed variable in the default branch and the compiler rejects it the moment a new variant is added anywhere in the codebase. This turns adding a state from a hunt through the repository into a list of build errors that stops when the work is done. It costs three lines. Engineers who have maintained a growing state machine put those three lines in without being asked.
Type predicates and assertion functions
Sometimes narrowing needs a function, and the language provides two ways to write one. A predicate returns a boolean and tells the checker what is true when it is true. An assertion function throws instead, and narrows everything after the call. Both are useful and both are unsound in the same way: nothing verifies that the body actually performs the check its signature claims. That makes them a good interview topic, because the answer you want acknowledges the hole rather than presenting them as free safety.
Generics That Earn Their Place, and Type Gymnastics That Do Not
There is a stage in learning this language where the type system becomes a puzzle and the puzzle is fun. Recursive conditional types, template literal manipulation, arithmetic performed on tuple lengths. It is genuinely impressive and it belongs almost nowhere in application code. The senior signal is not what someone can express. It is whether they stop, and whether they can explain the point at which the next person to open the file becomes the constraint that matters more than the elegance.
When a generic is doing real work
A generic earns itself when it preserves a relationship the caller cares about. A function that reads a key from an object and returns whatever that key holds needs one, because without it the caller gets a union of every value type and has to narrow something that was never ambiguous. A cache wrapper that returns what it stored needs one. A function with a single type parameter used once, in one position, does not, and that pattern usually means someone reached for a generic where a plain parameter was the answer.
Constraints and where inference happens
An unconstrained type parameter can be anything, so the body can do almost nothing with it. Adding a constraint says what the function needs and improves both the error messages and the editor experience for everyone downstream. The related skill is knowing where inference actually happens, because a parameter that appears only in the return position has nothing to infer from and silently falls back to its constraint. Debugging that is a rite of passage, and someone who has been through it explains it in plain language rather than reciting rules.
Conditional and mapped types belong in libraries
The economics are straightforward. A shared package used by forty files can justify a type that takes an hour to understand, because that hour is paid once and the benefit lands forty times. The same type sitting in a route handler is a tax on everybody who touches that route for the next two years. We ask candidates where they would draw that line and why. There is no single correct boundary, but the absence of any boundary at all is a maintenance problem waiting to happen.
The review question we ask
Given a piece of type level code, what breaks if we delete it and use a simpler type instead? A good answer names something concrete, usually a class of caller mistake that the simpler version would allow through silently. A weak answer is that the current version is more precise, which is true of nearly every complicated type and is not by itself a reason. Precision has a price and the price is paid by whoever reads the error message at two in the morning.
The Boundary Problem: Every Type Is Erased Before Your Code Runs
There is one idea here worth carrying into your next candidate conversation, and this is it. Types exist for the checker and are gone by the time anything executes. There is no runtime check, no shape verification, nothing left in the output but the JavaScript you would have written anyway. So every value that crosses into your program from outside is untyped in reality and typed only by assertion. API responses. Form fields. URL parameters. Environment variables. Anything read off disk or out of a queue. Teams that miss this get a typed codebase with exactly the same crashes as before, and no idea why.
Your API response type is a claim, not a check
Write an interface describing what an endpoint returns, annotate the fetch result with it, and the compiler is satisfied forever. It has verified nothing. It cannot. The payload arrives while your program runs and the checker finished its work before the build finished. When the upstream team renames a field or starts returning null for something that was always present, your code walks into it at full speed and the stack trace points somewhere three functions away from the actual cause. This is the most common source of production incidents on typed frontends we are asked to look at.
Form input, query strings and environment variables
Values from a form are strings until proven otherwise, including the one your type says is a number. A query parameter can appear twice and arrive as an array. Environment variables are strings or missing, and a config object that declares a port as a number is lying about what the platform hands over. Each of these is a small thing, and each has taken down a deployment because somebody trusted an annotation. Ask a candidate how they type their config loader. The answer is unusually revealing for such a small piece of code.
Schema validators and where to put the parse
The established fix is to declare a schema with a runtime validation library and derive the static type from it, so the check and the type cannot drift apart. Zod is the common choice and its inference is good enough that most teams never write the interface separately. Valibot trades some ergonomics for a smaller bundle, which matters on a client. io-ts and ArkType take different approaches to the same problem. The tool matters less than the placement: parse once at the edge, return a typed value, and let everything inside the application trust it.
Generating types instead of writing them
Where a machine readable contract already exists, generate. An OpenAPI document produces client types, a GraphQL schema produces operation types, and an ORM schema produces model types that update when a migration runs. Generation removes the drift between what the server sends and what the client believes, which is the whole failure mode. It does not remove the need to validate untrusted input, and a candidate who thinks generated types are a substitute for parsing has confused a build time convenience with a runtime guarantee.
Declaration Files and the Dependency That Ships No Types
Every project of any age has one. An older package with no bundled types, a fork somebody made internally, a vendor SDK distributed as a single minified file. What a team does at that moment is a decent proxy for its standards. The easy route is a cast, and the codebase carries an unchecked hole from then on. The route that takes an extra hour is a declaration file covering the parts actually used, checked into the repository, extended when someone needs more.
DefinitelyTyped and its failure mode
Community maintained declarations published under the types namespace cover a huge amount of the ecosystem and are usually the right first stop. The catch is that they version independently of the library they describe, so a package can be upgraded while its declarations stay behind, and the compiler will confidently describe an API that no longer exists. That produces the worst kind of error: a green build and a runtime failure. Checking whether declaration versions track their libraries is a five minute audit that nobody does.
Writing the smallest declaration that works
You do not need to describe a whole library. You need the four functions your application calls, with the arguments it passes and the values it uses. A short declaration file, kept next to the code and updated when usage grows, is honest about what has been verified and cheap enough that people will actually write it. Blanket declaring a module as any is the same shortcut wearing a different hat, and it is worth calling out in review for exactly that reason.
Module augmentation and declaration merging
When a framework's own types need extending, adding fields to a request object or a session, the language supports it directly through declaration merging. Done properly this is invisible and pleasant to use. Done carelessly it produces globals nobody can find the source of, and a new engineer spends an afternoon working out where a property came from. Ask a candidate to describe a time they augmented a third party type and how they made it discoverable. The good answers involve a comment and a predictable file location.
skipLibCheck, and what you give up
This option tells the compiler not to check declaration files, and most projects have it on because two dependencies with conflicting declarations will otherwise stop your build over something you cannot fix. That is a reasonable trade. It is also worth knowing you have made it, because real conflicts between your dependencies now go unreported. The candidate answer to look for is that it is a pragmatic default rather than a correct one, and that it gets revisited when a strange error appears.
Build and Tooling: tsc, esbuild, swc and Why CI Has to Type Check
Modern toolchains split a job that used to be one thing into two, and a surprising number of teams do not realise it has happened to them. Producing JavaScript and verifying types are now usually separate processes run by separate tools. Fast bundlers do the first and skip the second entirely. If nothing in your pipeline runs the checker, your type annotations are documentation with a syntax error risk, and the discipline you paid for exists only in the editors of whoever remembers to look.
Transpiling is not checking
esbuild and swc are fast precisely because they delete type annotations without understanding them. They parse a file, drop the parts that are not JavaScript, and emit output, all without building the cross file model that type checking requires. This is the correct design for a bundler and a disaster as a safety net. Your application will build, deploy and start with type errors sitting in it, and nobody will know until behaviour disagrees with the annotation in front of a user.
isolatedModules and the constraints it brings
Because those bundlers compile one file at a time with no knowledge of the others, some language features stop working. Re-exporting a type without marking it as a type export leaves a runtime import of something that does not exist. Certain enum forms and namespace patterns break the same way. Enabling isolatedModules makes the compiler reject the constructs your bundler cannot handle, so the failure arrives at build time. Any candidate who has migrated a project to a fast bundler has met this, and will say so quickly.
Keeping the check fast enough that people run it
Type checking is slow on large projects and slow checks get skipped. Incremental builds cache the previous result so only affected files are rechecked. Project references split a repository into units that build and check independently, which is what keeps a monorepo usable rather than a twelve minute wait on every commit. When a developer tells you the editor takes ten seconds to update after a keystroke, they are describing a project structure problem, and it is worth asking what they did about it.
Lint rules that catch what the compiler allows
The type aware rules in the TypeScript ESLint set find things the compiler is content to accept: floating promises never awaited, unsafe member access on a value that turned out to be any, unnecessary conditions on values that cannot be null. These need a project configured lint run, which is slower, and teams disable them for that reason and lose the coverage. Floating promises alone are worth the cost. They are the source of the async bug that appears only under load.
Sharing Types Across a Monorepo Is Where TypeScript Pays Off
Everything above is defensive. This part is the actual argument for adopting the language, and it is the one that changes what a team can do rather than what it can avoid. When your browser code and your server code live in one repository and share a package of type definitions, the contract between them is written once and checked on both sides by the same compiler. Renaming a field on the server produces an error in the component that reads it, before anyone opens a pull request. No other technique in the ecosystem gives you that for the price of a build step.
One definition, two consumers
The shape of an order, the set of permitted statuses, the payload of a webhook: defined in a shared package, imported by the API that produces it and the client that consumes it. The version that is merely copied between two repositories works fine for about four months and then diverges, usually in a field that is optional on one side and required on the other. We have been called in to fix that specific bug more than any other in this category, and it is always the same shape.
Project references and build order
Sharing types across packages needs the compiler to understand the dependency graph, and project references are the mechanism. Each package declares what it depends on, the build runs in the right order, and each unit is checked independently rather than as one enormous program. Getting this configured correctly is fiddly, involves composite settings and declaration output, and is exactly the kind of work that a strong candidate has scars from. It is also a fair interview topic because there is no way to fake having done it.
End to end inference, and its caveat
Libraries that infer client types directly from server route definitions take this further, removing even the shared interface. When frontend and backend deploy together from one repository, the ergonomics are excellent and the class of contract bug largely disappears. The caveat is worth stating plainly: this is a compile time link between two things that are separate at runtime, so an older client talking to a newer server is still an unvalidated boundary. The type system cannot see across a network and never could.
Deploy skew is the thing that bites
Two artefacts built from one commit will disagree the moment they are deployed at different times, which is most of the time. A browser tab left open across a release is running last week's client against today's API. Shared types make the contract explicit, which is a real improvement, but they do not version it. Handling removals as two deploys rather than one, and validating requests on the server regardless of what the client claims, is what actually keeps this safe. Candidates who mention it unprompted have operated something.
How Do You Screen a TypeScript Developer in an Hour?
Take home tasks are slow, and they mostly measure how much unpaid weekend a candidate can spare. For this specific skill you do not need one. The habits that matter are visible in how someone reads code they did not write, and an hour spent watching that is worth several days of waiting for a submission. Here is the shape of the session we run, which you are welcome to copy whether or not you ever speak to us.
Give them a file, not a puzzle
Prepare one file of about a hundred lines with four defects planted in it. A fetch result annotated as a domain type with no validation. An explicit any hiding a genuine mismatch. An interface with five optional fields that should have been a union of two shapes. A promise inside a loop that is never awaited. Ask what they would change and in what order. Priority is the signal. A candidate who fixes formatting before the unvalidated boundary is telling you what they have been rewarded for.
Ask about a migration they lived through
Most engineers with real experience have converted something. Ask which flag caused the most pain, how many files were in flight at once, and what they excluded and never came back to. Specific answers come with specific irritations attached, and you will hear them. Vague answers describe a process that sounds like the documentation. It is worth asking what they would do differently, because the honest reply usually involves having been too ambitious in the first fortnight.
The boundary question, asked directly
Where in your last codebase did untrusted data become typed data, and what happened there? You are listening for a place. A parsing layer, a schema, a set of guards at the controller edge, something. An answer that treats the annotation itself as the protection is the clearest possible signal that this person has not yet had the incident that teaches otherwise. They may still be a fine hire for a junior role. They should not be the one designing your API client.
Red flags worth naming
Casting through any to satisfy the compiler and describing it as normal. Being unable to explain what strict mode changes. Treating unknown as an inconvenience rather than a tool. Enthusiasm for type level cleverness with no view on when it is too much. And the quietest one: no opinion at all about the compiler configuration of a project they worked in for two years, which usually means they never looked outside the files they were assigned.
Three Situations We Are Asked About Most
What follows is composite: recurring shapes assembled from the briefs that reach us, never a record of a named client engagement. They are here because the same three shapes keep repeating, and recognising which one you are in changes the seniority you should be hiring for.
The migration that stalled at sixty percent
A JavaScript application, several years old, where a previous team started a conversion and left. Half the files carry the newer extension, strict mode is off, and there is a shared utilities module everything imports that is still untyped, so its any leaks into every consumer. Symptom: the team reports that typing has bought them nothing, which from where they sit is true. The work is unglamorous. Type the shared module first because it is upstream of everything, put a lint rule in place so nobody adds new untyped files, then enable noImplicitAny and clear it before touching strictNullChecks. The hire is mid to senior, needs patience more than brilliance, and needs to be comfortable making very small pull requests for several weeks.
The typed frontend that still crashes on real data
Everything is annotated, strict mode is on, the team is proud of the codebase, and users are still seeing the error boundary. Almost always the cause is at the edge. Responses from a partner service are annotated by hand and never checked, and the partner has started returning null in a field that was documented as always present, or an array where a single object used to be. Nothing in the build can see this. The fix is a parsing layer at every external call, types derived from those schemas rather than written alongside them, and logging that captures the raw payload when validation fails so the next incident takes minutes instead of days. This one needs someone senior enough to argue for the work, because it looks like rework to a product manager.
Two repositories and a contract nobody owns
The frontend and the API are separate repositories with separate teams, and the shapes are defined twice. They match on the day they are written. Six months later an optional field on one side is required on the other, a status string has gained a value the client does not handle, and integration bugs appear in the week after every release. Consolidating into a monorepo is the clean answer and is frequently not politically available. The fallback is a generated contract, from an OpenAPI document or a schema package published from the service and consumed as a dependency, with a build step that fails when the two drift. Whoever takes this on spends as much time on build wiring and negotiation as on TypeScript itself.
How Offshore TypeScript Work Runs From India
This is the part most pages skip or answer with a slogan. Distance is a real constraint and it is worth being specific about, because the way you run a typed codebase across time zones is genuinely different from running one down the corridor. The compiler helps here more than people expect. A build that fails on a contract change is a form of communication that does not need anybody awake.
Do the clock maths before you plan anything
Our offset is UTC plus five and a half hours with no seasonal adjustment, which means the figures stay fixed on this side of the world and shift on yours. Take a working day here of 09:30 until 18:30: in UTC terms that runs 04:00 until 13:00. For London that overlaps your morning by four or five hours depending on the season, which is comfortable. For New York it is nothing at all in summer, because your nine o'clock is the moment our day ends. Sydney gets two or three hours late in your afternoon, depending on which side of the Australian summer you are on.
What a shifted day costs, honestly
The fix for a US team is moving the engineer later, something like 13:30 to 22:30 India time, which puts four hours against your morning. That is real and it works. It is also somebody's evening, every evening, and pretending otherwise produces attrition around month five. We would rather agree the window with you before anyone starts, write it into the arrangement, and rotate it if the work genuinely needs more coverage than one shift provides. Continuous coverage is not a free feature, it is a rota with a cost attached.
Code review is the control, not the status call
With a narrow overlap the pull request becomes the main channel, so it has to carry more than a diff. We ask for context in the description, the reasoning behind a modelling decision, and a note where something was left deliberately loose. A typed codebase suits this well, because a reviewer eight hours away can see from the signature what changed about the contract without running anything. Daily written standups go into the same place as the work, so your morning starts with the state rather than a request for it.
What done means for typed code
We agree this at the start rather than discovering it at the first disagreement. Our default is that a change is done when the checker passes with no new suppressions, tests cover the states the union describes, any new external boundary has a schema, and the pull request explains why the type is shaped the way it is. If your team has stricter rules, we adopt yours. The point is that it is written down somewhere both sides can point at.
Getting from a conversation to a first commit
The engineers are already with us instead of being recruited after the brief lands, so matched profiles reach you within 48 hours of us understanding the role. From there, most engagements are working inside 7 days, and the opening days go on credentials, local environment and reading code rather than producing any. If your onboarding needs security clearance or hardware from your side, that timeline is yours to control, not ours.
Risks Worth Naming Before You Sign Anything
Offshore engineering has failure modes and you have almost certainly heard about them from someone. We would rather put ours on the page than have you discover them in month three. None of these are solved by a clause. They are solved by agreeing the mechanism early and then actually running it.
When the person turns out to be wrong for you
It happens, and pretending otherwise would be dishonest. Nobody gets one name pushed at them with an instruction to cope: you shortlist from a pool and run your own interviews before anything begins. If the person still turns out to be wrong for the codebase or the team, we provide a replacement within 48 hours. Handover matters as much as speed, so we plan for the outgoing engineer to write down what they know while the incoming one reads it, rather than treating the swap as a clean substitution.
Who owns the code, and the types
Ownership and assignment of intellectual property belong in the agreement, signed before the first commit, and we will not tell you what it says on a marketing page. What is worth flagging is the part specific to this work: a shared types package produced during an engagement is your asset in the same way the application is, and it should be named as such rather than left implied. Have your counsel read it. Ours will have read it too.
Access, devices and data
Repository access, cloud permissions, whose laptop the code sits on and whether production data ever reaches a development machine are decisions you should make rather than inherit. For typed work there is a small extra consideration: fixtures and test data often get committed to make the checker happy, and real customer records have reached repositories that way. We would rather generate fixtures from schemas. If you have regulatory obligations, tell us what they are early enough to design around, and get your own compliance view on them.
Overheads a proposal will never show you
Ramp up on an unfamiliar codebase is real work and the first fortnight is slower than the fourth. Someone on your side has to review pull requests, and if that person is already the bottleneck then adding capacity offshore will not help until they are unblocked. Meetings that used to happen at a desk now need writing down. These are not reasons to avoid distributed teams. They are reasons to plan for a slower first month than a proposal implies.
Engagement Models
Three shapes account for most of what lands in our inbox. Picking between them turns less on budget than on two questions: where technical leadership sits, and how sharply the work is already defined.
An engineer inside your team
Your backlog, your standups, your definition of done. The engineer works to your process and your architect makes the calls. This suits a codebase that is already typed and needs sustained contribution rather than direction, and it puts the review burden on your side, so it works best when you have someone with the time to do that well.
A small team with its own lead
For scoped work such as a migration, a shared types package or a rebuilt API client, where you want an outcome rather than daily involvement. The lead handles internal review and brings you decisions rather than questions. You still need someone on your side who can say yes, but the day to day coordination cost is much lower.
Review and remediation
A recurring block of time aimed at a specific problem: unpicking accumulated any, getting strict mode on, adding validation at boundaries, making the check fast enough that people stop skipping it. Useful when your team knows what needs doing and has no capacity to do it. Progress is measured against the counts we agree at the start.
Which Page Should You Actually Be On?
Since the typing habits described above are a filter rather than a role, the useful next step is usually the page for the framework your code is written in. Everything on this page still applies to the screening; the framework page covers the rest of the job, which is most of it.
If your codebase is a browser application
For component work, state management and the typing patterns that go with them, see hire React developers in India. If you are on the full stack framework with server components and route handlers, hire Next.js developers in India is the closer match, and it is where the shared types argument tends to land hardest. Teams on the other major framework should start at hire Angular developers in India, where TypeScript has been the default since the beginning rather than an addition.
If the typed code runs on a server
API services, queue workers and anything holding a database connection call for runtime knowledge that the type system does not touch, so hire Node.js developers in India covers the part of the job this page does not. If you are earlier than that and still working out what the team should look like, hire developers in India is the broader starting point. And if none of it is obvious yet, describe the codebase to us and we will tell you which of these we would send.
Frequently Asked Questions
Is hiring a TypeScript developer different from hiring a JavaScript developer?
It is the same person with an extra habit, and the habit is what you are paying for. Everyone in the pool writes JavaScript. The difference is whether they model the states their code can actually be in, or whether they annotate the happy path and cast their way through everything else. That habit shows up in a code reading exercise inside twenty minutes, long before a take-home task would come back.
What is the fastest way to tell whether a candidate really knows TypeScript?
Show them a function that fetches JSON and returns it annotated as a rich domain type, then ask what the compiler has verified. The answer you want is nothing, because the annotation is an assertion about data that arrives at runtime and the checker never sees. Candidates who spot that have been burned by it. Candidates who say the return type looks fine have used TypeScript for autocomplete.
Should we turn on strict mode in an old codebase, and what happens if we do?
Yes, but as a ratchet rather than a switch. Enabling the whole strict family at once on a large project produces an error count nobody will read and a branch that rots. Turn on noImplicitAny first and fix what it finds, then strictNullChecks, which is the flag that actually stops undefined reaching production. Keep each step small enough to merge inside a sprint.
Do types protect us from bad data coming out of an API?
No, and this is the single most expensive misunderstanding on typed projects. Types are removed before the code runs, so an interface describing a response is a promise made by whoever wrote it, not a check performed on the payload. Protection comes from parsing the payload at the boundary with a schema validator and deriving the type from that schema, so the two can never disagree.
Our build uses esbuild and is very fast. Do we still need tsc?
Yes, because esbuild and swc strip type annotations rather than verify them. That is exactly why they are fast. Your bundle will build cleanly with type errors sitting in it, and the first person to notice will be a user. Run a separate no-emit type check as a required step in continuous integration and treat a failure the same way you treat a failing test.
Can a TypeScript developer in India work useful hours with a US East Coast team?
Only if the shift is designed for it. India runs at UTC plus five and a half hours all year with no daylight saving, so a normal 09:30 to 18:30 day in Mumbai finishes at 13:00 UTC, which is 09:00 in New York during summer time. The overlap is zero. Shifting the engineer later, for example 13:30 to 22:30 India time, buys roughly four hours of your morning and costs them their evening, so agree it before anyone starts.
How do we stop the codebase drifting back to any after six months?
Make the drift visible and make it cost something. A lint rule that flags explicit any as an error with a required justification comment turns a silent shortcut into a review conversation. Track the count of suppression comments over time, the way you would track failing tests. The number going up is a real signal about schedule pressure, not about developer skill.