AI Engineer + Data Scientist
UST (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 30–45 LPA
Posted on 9 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 Retrieval-Augmented Generation (RAG) pipelines including chunking, hybrid search, re-ranking, memory, and tool orchestration.
- Deploy, monitor, and maintain AI workloads on Azure Kubernetes Services with CI/CD, observability, and implement responsible AI guardrails such as prompt-injection defense and content filtering.
Minimum Requirements
- 5+ years of ML/AI engineering experience with production-level large language model (LLM) and agentic AI delivery.
- Advanced Python programming skills and experience with at least one agent framework (e.g., LangGraph, AutoGen, CrewAI, PydanticAI).
- Expertise in LLM and prompt engineering (GPT, Claude, LLaMA) including hands-on experience with RAG workflows.
- Experience with Azure AI stack (Azure OpenAI, AI Search, AI Services), containerized deployment (Docker/Kubernetes on AKS/ARO), Databricks ML tools, version control, and CI/CD pipelines.
Ideal Candidate Profile
- Hands-on builder focused on delivering measurable business impact through production AI deployments (portfolio of 3+ deployments).
- Strong operational focus on end-to-end AI system design including responsible AI practices and performance/cost evaluation metrics.
- Experience working within agile environments deploying scalable AI solutions on Azure cloud with strong engineering discipline in CI/CD and container orchestration.