Industry or company preference: Product based or startup is preferred.

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.

- Valuable documentation and collaboration skills.

- Bias toward owning the whole problem: product, architecture, implementation, and

operations

📌 Staff AI Engineer (Chennai)
🏢 NXT Door Retail
📍 Chennai