Engineering & AI Recruitment in India
Technical quality matters. Hire AI engineers, ML engineers, backend developers, and data engineers in India through dedicated search. Talhive finds, assesses and closes engineers across AI, ML, backend, data, and platform who have built and shipped production systems for global companies building India teams.
- Executive search across six engineering sub-practices
- Assessed against twelve dimensions per candidate
- 90-day replacement guarantee on every placement
The quality of a search is determined early. Start with the role, the context, and what a strong hire looks like at 12 months.
Your details are held in strict confidence and are not shared with third parties.
Received.
A senior team member will review your enquiry and respond directly.
Four ways engineering and AI hiring fails in India.
Every one of these is decided before the first candidate conversation, which is why they are so expensive to discover late.
Sourcing from the label pool, not the production pool
Searching for engineers who call themselves AI engineers produces thousands of candidates with ML course certificates and notebook experience. The thesis must be built around production deployment evidence before outreach begins.
Anchoring compensation to 2022 or 2023 survey data
India’s AI engineer compensation has moved by 20% to 35% since 2022. Offers anchored to published surveys are below market before they are even extended. Live market testing before the search launches is the only way to avoid offer-stage failures.
Treating AI engineers as generic senior engineers
Production AI engineers have specific motivations: technical challenge, ownership of the model infrastructure, and the ability to influence product direction. Generic engineering offers (good salary, good team, interesting product) do not differentiate. The technical problem must be specific.
Not separating research from production experience
India has a strong research AI community at institutions like IISc and TIFR. Research experience is not production experience. The assessment must explicitly test for shipping under constraint (deadline, cost, reliability), not research quality.
Technical quality matters. Hire AI engineers, ML engineers, backend developers, and data engineers in India through dedicated search. Outreach second.
Each of those four failures is corrected before the first approach goes out. Every search to hire AI engineers from India begins with a sourcing thesis built around verifiable shipping evidence: specific products, infrastructure decisions, and production scale. The outreach is built around your specific technical problem, not a generic role description. Candidates receive one specific, technically credible approach, not a form letter.
Pressure tested before outreach.
We pressure test the role, success outcomes, reporting context, compensation and non-negotiables before outreach begins. The brief is the search.
Where the right people already work.
We identify where the right people already work, why they may move, and the proposition that will earn their attention. A 20K+ curated pool, mapped against 140+ target firms per mandate.
Beyond the CV, against twelve dimensions.
Every shortlisted candidate is assessed on motivation, operating style, scale fit, stakeholder maturity, execution history and retention risk. Maximum five shortlisted profiles per mandate.
From offer to month three.
We manage candidate conviction, offer risk, references, counteroffer dynamics and the first ninety days of onboarding. The hire is not complete at signature.
If that is how you want your next AI hire run, the quickest way in is a short conversation about the role and where the search has stalled.
AI, ML, backend, data, and founding engineers Talhive places in India.
Every profile is assessed against production deployment evidence. Where Talhive runs a dedicated practice for a role, the card links to it.
AI Engineers
Production LLM applications, RAG pipelines at real query volume, and ML-powered features users depend on.
You are hereMachine Learning Engineers
Model training, evaluation and MLOps for teams running machine learning in production.
ExploreData Scientists
Experimentation, modelling and analysis for teams where the question comes before the model.
ExploreData Engineers
The pipelines, warehouses and streaming infrastructure that production AI depends on.
ExploreAI Product Managers
Product leaders who have shipped AI-native products, not PMs who added AI to a title.
ExploreFounding AI Engineers
Zero-to-one ownership profiles for teams building an AI product from nothing.
ExploreIf the role you need is on this list, or sits close to it, we can scope the search directly from your brief.
What a retained, production-first search actually gives you.
Production-first search
The thesis is built on verifiable shipping evidence, not job titles or certifications.
Passive market mapping
Mapped against 140+ target firms per mandate, reaching people who are not applying.
Proprietary talent pool
A 20K+ curated pool built over nine years of senior technology search.
Technical assessment
Twelve dimensions covering motivation, scale fit, execution history and retention risk.
Written candidate intelligence
Every shortlist arrives with written synopses, not a forwarded CV.
Maximum five profiles
A shortlist you can actually act on. Volume is not the product.
Senior team involvement
A founder responds to every brief and stays close to the mandate.
Post-placement support
90-day replacement guarantee on every placement on every placement.
The same market. Two very different searches.
Where a conventional recruitment or contingent search firm and a Talhive mandate actually diverge, stage by stage.
The rest of your technology hiring plan.
AI hiring may be only one part of it. These are the other ways Talhive helps companies build and scale teams in India.
India Team Build
Building an engineering team in India from zero. City selection, leadership-first sequence, employer brand.
ExploreExecutive Search
Executive search for Staff, Principal and AI Lead mandates, with written intelligence briefs.
ExploreEmbedded RPO
An embedded recruiter inside your team, owning pipeline and hiring operations end to end.
ExploreEngineering & AI Hiring
Talhive’s full engineering practice, assessment dimensions and gate criteria.
ExploreProduct Hiring
Product managers and product leadership for teams where the roadmap drives the engineering plan.
ExploreDesign Hiring
Product designers and design leadership for teams building interfaces people keep using.
ExploreThe AI engineer label is everywhere. The production signal is not.
Finding engineers who have actually shipped is the real challenge when you hire AI talent in India. It requires a sourcing thesis built around shipping evidence, not self-identification. Since 2023, the number of engineers in India who self-identify as AI or ML engineers has grown faster than the number with production deployment experience. That distinction is where every failed AI engineer search went wrong, and it is the first thing companies looking to hire AI engineers in India have to get right, before outreach begins rather than after three interview rounds.
Engineers who call themselves AI engineers on LinkedIn. Includes notebook practitioners, ML bootcamp graduates, and engineers who have worked adjacent to AI teams. Large. Not what you need.
Engineers who have deployed production LLM applications, built RAG pipelines at real query volume, or shipped ML-powered features that users actually depend on. 2,000 to 4,000 individuals nationally. Accessible only through targeted outreach.
NBA India Technology Team. Zero attrition.
Built the NBA's India technology team in Mumbai. 100% offer acceptance. Zero attrition at 12 months. Leadership-first sequencing.
Read the NBA case studyMost searches that reach us have already stalled somewhere. Tell us where yours is and we will come back on whether the India production pool actually fits the role.
Brief to signed offer. Six weeks.
What happens from day zero to day ninety, stage by stage.
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Day 001
Calibrate.
- Mandate architecture and stakeholder alignment
- Success outcomes, comp reality and decision process
- Target company universe and candidate thesis
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Day 702
Map & engage.
- Passive market mapping across relevant talent pools
- Role narrative for senior candidates, not generic outreach
- Early compensation, motivation and counteroffer checks
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Day 2103
Shortlist & decide.
- Evidence-led shortlist with written synopses
- Structured interviews and feedback cadence
- Fit, risk, compensation and close probability aligned
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Day 4504
Close & protect.
- Offer strategy, references and counteroffer management
- Notice period tracking and joining confidence
- Post-placement support and replacement protection as agreed
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Day 90
Where the talent is, and what the market costs.
of India’s production AI engineers
primarily enterprise and cloud AI
applied ML, data science adjacent
Bands reflect what is required to move a strong passive candidate. All-in compensation including ESOP should be modelled. Survey data lags the market by 12 to 18 months; live calibration is required before first outreach.
Best Bengaluru source companies
Engineers who have shipped production AI at consumer scale: Swiggy (recommendation, ETA prediction), Meesho (catalogue AI, pricing), PhonePe (fraud detection, credit underwriting), Razorpay (risk models), CRED (personalisation), and the Bengaluru offices of Google, Microsoft and Amazon with AI infrastructure exposure.
What the outreach narrative must contain
Production AI engineers in India receive many approaches. The ones that get responses are specific: the technical problem, the current production architecture, what the candidate will own, and why this is a harder or more interesting problem than what they are working on now. Generic “exciting AI opportunity” approaches are deleted. This is why standardised templates fail when you try to hire AI engineers in India at the senior end of the market.
We do not just send CVs.
What is covered before a profile reaches you, and what happens after the offer is signed.
Twelve dimensions, before shortlist
Motivation, operating style, scale fit, stakeholder maturity, execution history and retention risk, all assessed before a candidate reaches your calendar.
Shipping record, not job titles
Specific products deployed, user-facing features shipped, and infrastructure built for production inference, all verified rather than self-reported.
A written synopsis per profile
Maximum five profiles per mandate, each with a written synopsis covering fit, risk, compensation position and close probability.
90-day replacement guarantee on every placement
Every placement carries a ninety-day replacement guarantee, plus notice-period tracking and onboarding support through month three.
Dedicated, not contingent
A dedicated mandate buys mapping, calibration and targeted engagement of passive candidates, not a race to forward the same CVs faster.
A founder on every mandate
A founder responds to every brief within 24 hours and stays close to the search through to close.
Questions companies ask before hiring engineers in India
Direct answers on cost, roles, and how we run the search. Anything not covered here is answered in a call.
Build your AI team with production-ready talent.
Tell us what you are building and what kind of AI talent you need. Talhive will come back with the sourcing thesis, the realistic compensation band, and whether the India production AI pool fits your requirement.
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