Ai Ml Engineer

Role & responsibilities

• Design, develop, and deploy scalable LLM, RAG, and Agentic AI solutions.
• Build production-ready AI agents and multi-agent workflows using LangGraph, CrewAI, AutoGen, or similar frameworks.
• Develop and optimize LLM inference, retrieval, and deployment pipelines for performance, scalability, and cost efficiency.
• Implement RAG pipelines, semantic search, embeddings, and vector database solutions.
• Apply prompt engineering, model evaluation, fine-tuning, and hallucination mitigation techniques.
• Develop scalable backend services and APIs using Python and FastAPI.
• Follow strong software engineering practices including TDD, concurrency, microservices, CI/CD, and code quality.
• Deploy AI solutions using Docker, Kubernetes, and cloud platforms such as AWS/Azure/GCP.
• Implement LLM observability, monitoring, evaluation, and MLOps practices.
• Collaborate with Data Science, Research, Product, and Engineering teams.
• Mentor junior engineers and contribute to architecture and technical decisions.
• Ensure secure, ethical, responsible, and production-ready AI development.

Preferred candidate profile

• 58 years of overall software/AI engineering experience.
• Strong hands-on experience in Python, LLMs, Generative AI, and Agentic AI.
• Proven experience building production-grade RAG and multi-agent systems.
• Strong expertise in LangChain and LangGraph; exposure to CrewAI/AutoGen is preferred.
• Experience with Hugging Face Transformers and LLM prompting/fine-tuning.
• Hands-on knowledge of PyTorch and/or TensorFlow.
• Strong understanding of vector databases such as FAISS, Pinecone, ChromaDB, Qdrant, or Azure AI Search.
• Experience with FastAPI, REST APIs, microservices, Docker, Kubernetes, and CI/CD.
• Exposure to AWS, Azure, or GCP, preferably SageMaker/Bedrock.
• Knowledge of LLMOps/MLOps, MLflow, model evaluation, and observability.
• Good to have: LLM quantization (GPTQ/AWQ), multimodal AI, MCP, Snowflake, Airflow.
• Strong problem-solving, communication, ownership, and mentoring skills.
• Bangalore-based or willing to relocate to Bangalore and comfortable working from office minimum 12 days/month.

Interested candidates please share CV At [email removed]