AI/Gen AI Engineer

Position: AI/Gen AI Engineer Location: Chennai - Onsite/Hybrid/Remote Engagement Type: Full Time Shift Timing: 1.30PM - 10.30PM IST (UK Shift Time) About the Role: We are hiring an AI / GenAI Engineer to build and deploy production agents on Google Vertex AI (now the Gemini Enterprise Agent Platform). You will work end-to-end — from prototyping with Gemini models and RAG, to building multi-agent workflows with the Agent Development Kit (ADK), to deploying on Agent Runtime with proper governance, evaluation, and monitoring. This is a hands-on engineering role with direct client and solution-design exposure. Key Responsibilities: - Design, build, and deploy enterprise-grade AI agents on Vertex AI / Gemini Enterprise Agent Platform (Model Garden, Agent Builder / Agent Studio, Agent Engine / Agent Runtime, Vertex AI Pipelines, Model Registry, Endpoints). - Develop GenAI applications using Gemini (3.x family) and other Model Garden models — prompt engineering, function calling, structured output, and model evaluation/tuning. - Build RAG pipelines using Vertex AI Search, Vector Search, RAG Engine, and embeddings; implement grounding against enterprise data sources. - Implement multi-agent orchestration using the Agent Development Kit (ADK), Memory Bank / Sessions, and the Agent2Agent (A2A) protocol; integrate tools via Model Context Protocol (MCP) servers. - Productionize models and agents with solid MLOps practices: CI/CD, Vertex AI Pipelines, model/agent monitoring, observability, and cost optimization. - Integrate AI services with enterprise systems and APIs (REST/gRPC, FastAPI) and wider GCP services (BigQuery, Cloud Run, Cloud Functions, Pub/Sub, GCS, Dataflow, GKE). - Apply enterprise governance and security — IAM, data privacy, and responsible-AI guardrails. - Partner with solution architects and client stakeholders to gather requirements, design solutions, and document deliverables. Required Skills & Qualifications: - 4–8 years of software/ML engineering experience, with hands-on Vertex AI / Gemini Enterprise Agent Platform (or equivalent GCP AI) project experience. - Strong Python programming; clean, production-quality code. - Practical experience building GenAI / LLM applications — prompting, RAG, embeddings, vector databases, and model evaluation. - Working knowledge of Google Cloud Platform core services (BigQuery, Cloud Run/Functions, GCS, IAM, Pub/Sub). - Experience deploying and operating models/agents in production (MLOps, containerization with Docker, basic Kubernetes/GKE). - Solid understanding of agentic AI concepts — tool use, multi-agent orchestration, memory, and agent governance. - Strong API design and integration skills (REST/gRPC, FastAPI). - Good communication and the ability to work directly with clients and cross-functional teams. Good-to-Have (Preferred): - Google Cloud certification — Professional Machine Learning Engineer or Professional Cloud Architect. - Experience with the Agent Development Kit (ADK), A2A protocol, and MCP integrations. - Familiarity with orchestration frameworks such as LangGraph, LangChain, or LlamaIndex. - Exposure to other AI stacks (AWS Bedrock, Azure OpenAI, Anthropic Claude) for multi-cloud / multi-model work. - Experience integrating AI with enterprise platforms (NetSuite, Salesforce, ERP/CRM systems). - Background in consulting / client-facing delivery environments. Education: - Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field (B.E. / B.Tech / M.E. / M.Tech / MCA). Equivalent practical experience also considered.