GenAI Engineer (Agentic AI + Vertex AI)

Job Title & Overview: GenAI Engineer (Agentic AI + Vertex AI) — We are seeking a hands-on Generative AI Engineer to design, build, and productionize agentic AI solutions on Google Cloud. You will develop LLM-powered agents, tool/function calling workflows, and retrieval-augmented generation (RAG) systems using Vertex AI, with a focus on reliability, safety, observability, and measurable business impact.

Location & Work Mode: Hybrid work model with team collaboration days; primary location is Bengaluru, Karnataka (India). Candidates should be comfortable working with distributed stakeholders and participating in architecture/design reviews.

Key Responsibilities:

• Design and implement agentic AI systems (multi-step planning, tool use, memory, and orchestration) for enterprise workflows (support, operations, analytics, automation).

• Build and optimize RAG pipelines using Vertex AI, vector stores, embeddings, and document processing; implement chunking, hybrid retrieval, and reranking strategies.

• Develop prompt engineering, function/tool calling, and structured output generation patterns; enforce schemas with validation and robust error handling.

• Implement evaluation frameworks (offline/online) for quality, safety, latency, and cost; define golden datasets, automated regression tests, and A/B experiments.

• Productionize GenAI services via APIs/microservices, CI/CD, and infrastructure-as-code; deploy on GKE/Cloud Run with scalable, secure configurations.

• Implement model/agent observability: tracing, prompt/version tracking, telemetry, dashboards, and incident response playbooks.

• Ensure security and compliance: data governance, PII handling/redaction, access controls (IAM), secrets management, and auditability.

• Collaborate with product, data, and platform teams to translate requirements into technical designs; mentor junior engineers and contribute to best practices. Required Skills & Experience:

• 4+ years of software engineering experience with at least 1–2 years building ML/GenAI solutions in production environments.

• Strong Python proficiency (FastAPI/Flask), async patterns, and packaging/testing (pytest).

• Deep experience with Google Cloud Vertex AI (Model Garden/Endpoints, GenAI APIs, pipelines, and permissions/IAM basics).

• Agentic frameworks and patterns (LangChain/LangGraph, LlamaIndex, tool/function calling, planners, memory, guardrails).

• RAG systems: embeddings, vector databases (Vertex AI Vector Search, Pinecone, Weaviate, FAISS), retrieval tuning, and grounding.

• API design and microservices; containerization with Docker; deployment on Cloud Run/GKE; CI/CD (Cloud Build/GitHub Actions).

• Data handling with BigQuery/Cloud Storage; streaming or messaging is a plus (Pub/Sub).

• LLM evaluation and safety: hallucination mitigation, prompt injection defenses, content filtering, and automated test harnesses. Education & Certifications: Bachelor’s degree in Computer Science, Engineering, or a related field preferred. Nice-to-have certifications include Google Cloud Professional Machine Learning Engineer, Professional Cloud Developer, or Generative AI on Google Cloud skill badges/certificates.

Additional Information: You’ll join a team that values pragmatic engineering, experimentation with measurable outcomes, and strong documentation. We offer competitive benefits, flexible hybrid work, learning budgets for cloud/AI certifications, and opportunities to lead end-to-end GenAI projects from discovery through production scaling. Estimated salary range for Bengaluru for this level is competitive and aligned with market benchmarks, based on skills and interview performance.