Role Description

Primary Skills: Agentic AI, Pytorch, RAG, ML, Gen AI Description: Key Responsibilities

Build and deploy scalable LLM, RAG, and agent-based systems
Architect LLM inference and deployment pipelines
Optimize models for efficient and cost-effective production
Collaborate with data science, research, and product teams
Ensure clean code, testing, reproducibility, and CI/CD
Mentor junior engineers and drive engineering best practices
Ensure ethical, secure, and responsible AI development Required Skills
Advanced Python with strong fundamentals in NumPy, Pandas, scikit-learn
Deep learning expertise in PyTorch / TensorFlow
Hands-on with LLM frameworks: Hugging Face Transformers, LangChain (prompting & fine-tuning)
Strong experience with Agentic AI frameworks: AutoGen, CrewAI, LangGraph
Expertise in RAG pipelines,



semantic search, vector databases
Strong software engineering practices: microservices, TDD, concurrency
Ability to rapidly prototype and productionize GenAI solutions Positive-to-Have Skills
Model optimization: Quantization (GPTQ, AWQ), pruning, distillation
Multimodal AI (text, vision, audio): CLIP, BLIP, Whisper, LLaVA
LLM serving using FastAPI and vector DBs (FAISS, Pinecone, Chroma)
CI/CD pipelines, Airflow, Docker, Kubernetes / Helm
Cloud AI deployments on AWS / Azure / GCP (e.g., SageMaker)
MLOps & tracking: Git, MLflow
Data pipelines & ELT/ETL using Snowflake

Skills

Python, PyTorch, Agentic AI, RAG

📌 Lead I (Bengaluru)
🏢 UST
📍 Bengaluru