AI Engineer + Data Scientist- Lead
UST (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 20–40 LPA
Posted on 10 Sept
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Job description
Structured overview of role & requirements
About This Role
- Build and deploy production-grade Generative AI and agentic AI applications automating enterprise workflows from design through deployment.
- Design and implement RAG pipelines including chunking, hybrid search, re-ranking, memory, and tool orchestration.
- Deploy and monitor AI workloads on Azure with CI/CD, implement responsible AI guardrails, and define evaluation metrics for task success, hallucination, latency, and cost.
Minimum Requirements
- 5+ years of ML/AI engineering experience with production LLM/agentic delivery.
- Strong hands-on skills with Python, agent frameworks (LangGraph, AutoGen, CrewAI, or PydanticAI), and prompt engineering (GPT, Claude, LLaMA).
- Experience with Azure AI stack, Databricks ML (MLflow, Delta Lake), vector databases (FAISS, Pinecone, Chroma), containerized deployments (Docker/Kubernetes, AKS/ARO), and CI/CD tools (Jenkins, GitHub Actions).
- Portfolio of 3+ production AI deployments demonstrating measurable business impact.
Ideal Candidate Profile
- Proven ability to architect and deliver complex AI systems involving RAG pipelines and agentic AI in enterprise settings.
- Experience working with Azure cloud AI services and container orchestration platforms with strong CI/CD discipline.
- Familiarity with deployment and monitoring of AI workloads including implementing AI guardrails and metrics to measure production effectiveness.