AI Engineer
Location: On-Site — Delhi, India Type: Full-time | Immediate Joiners Preferred
We're building a next-gen AI product that personalizes conversations at scale using Large Language Models. We're looking for a hands-on AI Engineer who can own LLM systems end-to-end — from designing agentic pipelines and writing the Python backend to engineering the prompts and evals that make the output reliable.
This is a build-from-scratch role. You should be comfortable across the whole stack: orchestration, retrieval, serving, and — critically — the prompt layer where most of the product's quality is won or lost.
What You'll Do
- Design and build agentic / multi-step LLM pipelines using LangGraph (or LangChain)
- Write production Python backends — FastAPI services, REST APIs, background workers
- Build and optimize RAG pipelines: retrieval, grounding, citation, context shaping
- Own prompt engineering as a core discipline — design, test, and version production prompts (system prompts, few-shot, chain-of-thought, structured JSON/XML outputs) and build the evals that keep them reliable
- Systematically reduce hallucination and improve grounded, citation-backed outputs
- Integrate vLLM, OpenAI, Anthropic, or open-source models for fast inference
- Containerize and deploy services with Docker
- Optimize latency, token usage, cost, and response quality
- Stay current with Generative AI & MLOps developments
Key Skills We're Looking For
- Strong prompt engineering — deep, hands-on command of few-shot, chain-of-thought, system-prompt design, structured outputs, prompt versioning, and an eval-driven approach (promptfoo, LangSmith, or custom). This is a must-have, not a bonus.
- Strong Python — clean, production-grade, not just notebooks
- LangGraph / LangChain — hands-on experience building agentic or multi-node pipelines
- LLM APIs — OpenAI, Anthropic, Hugging Face, Cohere
- RAG — vector databases (Pinecone, FAISS, Qdrant), retrieval and grounding
- FastAPI + REST API development
- Docker and containerized deployments
- Bonus: vLLM or other model-serving frameworks, streaming (SSE/WebSockets), MLOps tooling
Ideal Profile
- 2–4 years building AI/ML products (strong 1-year candidates with an exceptional portfolio considered)
- Proven projects or GitHub showing real LLM systems — agents, RAG, or chatbots that actually shipped
- A portfolio that demonstrates prompt craft: prompts, eval suites, or measurable quality improvements
- Curious, self-driven, and fast at turning ideas into working systems
- Excited to build AI that solves real business problems
Why Join Us?
- Build from scratch in a high-impact B2B AI product
- Work directly with leadership & product strategy
- Lean, execution-focused founding team
- Flexible setup, high ownership, fast iterations
How to Apply Send your resume and GitHub/portfolio to [email protected] Subject line: AI Engineer Application – [Your Name]
Job Types: Full-time, Permanent
Pay: ₹20,000.00 - ₹25,000.00 per month
Benefits:
- Commuter assistance
- Food provided
- Health insurance
- Internet reimbursement
Application Question(s):
- minimum 2 year as an AI developer
Experience:
- AI: 2 years (Required)
- Machine learning: 1 year (Required)
Work Location: In person
