Our AI practice ships systems with audit trails, cost ceilings, and evaluation gates - the unglamorous engineering that separates production AI from conference demos. Youll build RAG pipelines over messy enterprise data, agents that execute real workflows, and the harnesses that prove they work.

You should be the kind of engineer who asks how do we know its right before which model should we use

What you will do
Design and ship LLM applications: RAG platforms, copilots, document intelligence, agents
Build evaluation suites that gate releases on accuracy, safety, latency, and cost
Engineer data boundaries: what leaves the clients setting and what never can
Integrate AI into enterprise systems through governed, least-privilege interfaces
Track the model landscape and translate it into client-ready recommendations

What we are looking for
3+ years software engineering with robust Python or TypeScript




Shipped LLM features beyond prototypes: retrieval, orchestration, evaluation
Working knowledge of embeddings, vector stores, and prompt/context engineering
Transparent writing - your design docs get read by client architects

Nice to have
LangGraph or similar agent frameworks in production
Fine-tuning and model-serving experience (vLLM, GPU infra)
Classic ML background (forecasting, classification)

Apply Three conversations, and we tell you where you stand after each one.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Ai Engineer Llm Systems Noida
🏢 Brihat Infotech
📍 Noida