Data Scientist + AI ENgineer
UST (company site, opens in a new tab)5–7 yrsBengaluruOn-siteDirect career pageEst. 20–35 LPA
Posted 17h ago
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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 using LangGraph, AutoGen, CrewAI, or Semantic Kernel.
- Design and maintain Retrieval-Augmented Generation (RAG) pipelines and deploy AI workloads on Azure (AKS/ARO) with CI/CD and monitoring.
- Implement responsible AI guardrails and define evaluation metrics to track task success, hallucination, latency, and cost.
Minimum Requirements
- 5+ years of experience in ML/AI engineering with production LLM/agentic application delivery.
- Bachelor's or Master's in CS, Data Science, or related field (B.E./B.Tech or M.Tech).
- Strong skills in Python, familiarity with agent frameworks (LangGraph, AutoGen, CrewAI, PydanticAI).
- Experience with Azure AI stack, containerized deployment (Docker/Kubernetes), CI/CD tools (Jenkins/GitHub Actions), and version control (Git).
Ideal Candidate Profile
- Experienced ML/AI engineer with 5-7 years in production deployment of AI applications, particularly LLM and agentic AI.
- Hands-on with RAG workflows, prompt engineering, model fine-tuning, LLMOps/MLOps, and AI security compliance.
- Comfortable working independently as a technical individual contributor reporting to AI Technical Lead / Manager within enterprise environments, preferably with manufacturing or supply-chain domain exposure.