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.