AI Engineer / Developer

Snapshot

Experience: 5 - 9 years in ML/AI engineering

Reports To: AI Technical Lead / Manager, AIML

About the Role

Build and ship production-grade GenAI and agentic AI applications that automate enterprise workflows from design through deployment. A hands-on individual-contributor role for a solid builder.

Key Responsibilities
Build agentic applications using LangGraph, AutoGen, CrewAI, or Semantic Kernel.
Design RAG pipelines chunking, hybrid search, re-ranking, memory, and tool orchestration.
Deploy and monitor AI workloads on Azure (AKS/ARO) with CI/CD and observability.
Implement responsible-AI guardrails prompt-injection defense and content filtering.
Define evaluation metrics for task success, hallucination, latency, and cost.

Must-Have Skills
5+ years ML/AI engineering with production LLM/agentic delivery.
Advanced Python and at least one agent framework (LangGraph, AutoGen, CrewAI, PydanticAI).
Solid LLM and prompt-engineering skills (GPT, Claude, LLaMA); hands-on RAG workflows.




Azure AI stack (Azure OpenAI, AI Search, AI Services) and Databricks ML (MLflow, Delta Lake).
Vector databases (FAISS, Pinecone, Chroma) and embedding/retrieval design.
Containerized deployment (Docker/Kubernetes, AKS/ARO) and REST APIs / WebSockets / event-driven services.
CI/CD and version control (Jenkins / GitHub Actions, Git) with SDLC and agile practices.
Portfolio of 3+ production AI deployments with measurable business impact.

Nice to Have
Model fine-tuning (LoRA/PEFT), multi-modal AI, and model evaluation frameworks.
LLMOps / MLOps and model monitoring (drift, latency, cost, hallucination).
Knowledge graphs (Neo4j); AWS Bedrock / GCP Vertex AI exposure.
AI-augmented dev tools (GitHub Copilot, Claude Code, Windsurf) for rapid prototyping.
Enterprise AI security, compliance, and governance awareness.
Manufacturing or supply-chain domain experience.

📌 Hiring For Ai Engineer / Developer Bengaluru
🏢 Sass Innovations
📍 Bengaluru