Agentic AI / GenAI Engineer - JG

Experience Required

• 6+ years in AI/ML, data science, or software engineering

• 3+ years in GenAI, LLM, RAG, conversational AI, or ML productionisation

Key Responsibilities

• Build and deploy secure, production-grade AI agents using GenAI frameworks

• Develop APIs with Python (FastAPI, Flask, or similar)

• Implement RAG architecture: ingestion, chunking, embeddings, retrieval, ranking, grounding, citations, evaluation

• Apply LLM techniques: embeddings, vector search, prompt design, evaluation, hallucination control

• Manage MLOps/LLMOps: deployment, monitoring, evaluation, versioning, observability

• Ensure security and governance: IAM, PII handling, prompt injection risks, data leakage prevention, approval workflows

• Deliver working prototypes and production-ready services

Must-Have Skills

• Python, FastAPI, REST APIs, async processing

• LLM application development and RAG implementation with vector databases

• Prompt engineering, tool/function calling, structured outputs

• LLM security: prompt injection, guardrails, access control

• GCP Vertex AI, Gemini, Cloud Run, GKE, or equivalent

• Agent orchestration using ADK, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar

• Evaluation frameworks: Vertex AI, Evals, RAGAS, regression tests

Nice to Have (Trainable)

• Google Agent Development Kit (ADK)

• Gemini Enterprise Agent Platform

• Agent observability and tracing

• Multi-agent architecture

• Human-in-the-loop approval flows

• Enterprise knowledge graph / search integration

Short JD Data Scientists / GenAI Engineers with strong Python, LLM/RAG expertise, and production deployment experience.