Staff AI Engineer
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Before you apply
LocationChennai, India
Typefull-time
SeniorityLead
Experience15+ yrs
DepartmentTechnology
Company size501–1,000 people
First seenOct 16, 2026 · 2w ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
15+ years of software engineering, with recent hands-on ownership of production systems
Proven full-stack depth: can design and implement frontend, backend, APIs, data stores, and cloud infrastructure — not limited to AI-only work
Hands-on with AI-assisted development tools (Cursor, GitHub Copilot, and similar) as part of day-to-day engineering
Hands-on experience shipping LLM / GenAI or ML systems in production (RAG, agents, fine-tuning, evaluation, or equivalent)
Comfortable choosing and using the right stack for the problem (e.g. TypeScript/Python, React or similar, REST/GraphQL, SQL/NoSQL, queues, object storage)
Experience with CI/CD, distributed systems, and production debugging
Strong ownership: can take an ambiguous brief and deliver a working product end to end
Clear communication and the ability to work with product, design, and other engineers without hand-holding
Degree in Computer Science / Engineering or equivalent practical experience
Hands-on engineer with a production-level coding mindset — writes, reviews, and ships code
Track record of building scalable, reliable systems, not just prototypes or notebooks
Good documentation and collaboration skills
Bias toward owning the whole problem: product, architecture, implementation, and operations
Skills
React
Next.js
Node.js
Python
Go
TypeScript
REST
GraphQL
SQL
NoSQL
AWS
CI/CD
Cursor
GitHub Copilot
LLM
GenAI
RAG
ML
Benefits
Unlimited PTO
Wellness reimbursement
Commute reimbursement
Paid parental leave
Responsibilities
•
Own end-to-end delivery of AI-powered products — from problem framing and architecture through implementation, deployment, and production operations
•
Design, build, and ship full-stack systems: frontend, backend APIs, data layers, and AI/ML services — not just models or prompts
•
Take a product from idea to production independently: design APIs, build UIs, wire data flows, integrate models, and operate the system
•
Build and productionize LLM / GenAI features (RAG, agents, tool-calling, evaluation, guardrails) and integrate them into real user-facing applications
•
Design scalable application and model-serving architectures that are reliable, observable, and cost-aware
•
Own data pipelines, retrieval, embeddings, and evaluation loops so AI features stay accurate and measurable in production
•
Work across the stack as needed — React/Next (or equivalent), Node/Python/Go services, databases, queues, cloud, and CI/CD — without waiting on a specialist for every layer
•
Partner with product, design, and engineering to turn ambiguous problems into shipped features
•
Review code, raise the bar on system design, and mentor engineers on both AI and full-stack practices
•
Establish engineering standards for AI quality, evaluation, security, and release confidence
•
Debug production issues across the full path: UI, API, infra, data, and model behavior
Requirements
•
15+ years of software engineering, with recent hands-on ownership of production systems
•
Proven full-stack depth: can design and implement frontend, backend, APIs, data stores, and cloud infrastructure — not limited to AI-only work
•
Hands-on with AI-assisted development tools (Cursor, GitHub Copilot, and similar) as part of day-to-day engineering
•
Hands-on experience shipping LLM / GenAI or ML systems in production (RAG, agents, fine-tuning, evaluation, or equivalent)
•
Comfortable choosing and using the right stack for the problem (e.g. TypeScript/Python, React or similar, REST/GraphQL, SQL/NoSQL, queues, object storage)
•
Experience with CI/CD, distributed systems, and production debugging
•
Strong ownership: can take an ambiguous brief and deliver a working product end to end
•
Clear communication and the ability to work with product, design, and other engineers without hand-holding
Qualifications
•
Degree in Computer Science / Engineering or equivalent practical experience
•
Hands-on engineer with a production-level coding mindset — writes, reviews, and ships code
•
Track record of building scalable, reliable systems, not just prototypes or notebooks
•
Good documentation and collaboration skills
•
Bias toward owning the whole problem: product, architecture, implementation, and operations.
Perks:
•
Day off on the 3rd Friday of every month (one long weekend each month)
•
Monthly Wellness Reimbursement Program to promote health well-being
•
Monthly Office Commutation Reimbursement Program
•
Paid paternity and maternity leaves
About the company
Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most.