Senior AI/ML Engineer - LLM/RAG

Role : AI Engineer - Agentic AI & Production ML.Experience : 4 - 7 Years.

Education : Only IIT OR NIT OR BITS.

Role Overview :

We are looking for an AI Engineer to build and own production - grade AI systems end - to - end - from LLM applications and agentic workflows to model serving, evaluation, and monitoring.

The role requires strong hands - on experience in Agentic AI, LLM orchestration, self - hosted models, and production ML engineering.

Responsibilities : Agentic AI & LLM Systems (Must Have) :

• Build AI agents, LLM workflows, and orchestration systems.

• Develop RAG pipelines, memory systems, and retrieval workflows.

• Work with LLM gateways and agent frameworks.

• Improve reliability and performance of LLM applications.

Model Serving & Infrastructure (Must Have) :

• Deploy and optimize self - hosted AI models.

• Experience with vLLM / Triton or similar serving frameworks.

• Optimize latency, scalability, and inference cost.

• Work with Docker, Kubernetes, and cloud infrastructure.

AI Engineering :

• Build production AI systems using Python.

• Work with PyTorch, Hugging Face, Transformers, and vector databases.

• Own AI lifecycle : development - deployment - monitoring - improvement.

Evaluation & Observability :

• Build evaluation frameworks and benchmark datasets.

• Track AI quality, latency, cost, and reliability metrics.

• Set up monitoring, dashboards, and alerts for production AI systems.

Speech AI (Good to Have) :

• Experience with STT, ASR, speaker diarization, or voice AI systems.

Required Skills : Must Have :

• Agentic AI.

• LLM / Generative AI.

• LLM Orchestration.

• LLM Gateway.

• RAG.

• Vector Databases.

• Self - hosted Models.

• vLLM / Triton.

• Python.

• PyTorch.

• Hugging Face.

• Kubernetes.

• MLOps.

Good to Have :

• Speech AI / STT.

• RLHF.

• Reinforcement Learning.

• AI Evaluation.

• Open - source AI contributions.

Ideal Candidate Profile :

• Has shipped AI products into production.

• Strong understanding of LLM systems and AI architecture.

• Can own complete AI systems, not just model tuning.

• Demonstrates strong engineering fundamentals and problem - solving ability.

Hiring benchmark : Candidates should demonstrate strong Agentic AI depth, production ML experience, and ownership of scalable AI systems.