AI Engineering & Agentic Systems EngineerWe are looking for a hands-on AI Engineering & Agentic Systems Engineer with experience building production-grade AI applications using Large Language Models (LLMs) and multi-agent systems. This is an engineering role focused on developing scalable AI solutions, not a traditional Machine Learning or Data Science position.Required Experience:10+ years of software engineering experienceStrong Python programming experienceHands-on experience building production LLM-powered applicationsExperience with Agentic AI frameworks and tools: Google Agent Development Kit (ADK)LangChainLangGraphModel Context Protocol (ClientP/FastClientP or similar)A2A / ACP agent communication protocolsExperience with LLM APIs: Vertex AI / GeminiAWS BedrockOpenAIExperience with Retrieval-Augmented Generation (RAG)Multi-Agent orchestrationFunction Calling and Structured OutputsHuman-in-the-Loop (HITL) workflowsFastAPI and AsyncIOREST API developmentApache Kafka or GCP Pub/SubDocker and KubernetesCI/CD using GitHub Actions or Cloud BuildCloud experience (GCP preferred, AWS acceptable)Vector DatabasesPostgreSQL / SQLMongoDB, Firestore, or other NoSQL databasesGitAdditional Skills:TypeScript / JavaScriptTerraform or Infrastructure as CodeRedisOpenTelemetryGrafanaOpen Policy Agent (OPA)SPIFFE / Workload IdentityPrompt management and evaluation toolsResponsible AI and AI governanceAI observability and monitoringHealthcare or Insurance domain experienceResponsibilities:Design and develop AI-powered applications using LLMs and Agentic AI frameworks.Build multi-agent workflows using LangChain, LangGraph, and Google ADK.Develop scalable RAG-based applications with Vector Databases.Integrate enterprise systems using REST APIs, Kafka, and cloud services.Build reusable AI platform components for prompt orchestration, agent frameworks, and AI workflows.Develop production-ready AI services using Python, FastAPI, Docker, and Kubernetes.Implement monitoring, logging, evaluation, and governance for AI applications.Build automated CI/CD pipelines and deploy applications in GCP or AWS.Work closely with cross-functional teams to deliver enterprise AI solutions.Mentor developers and promote AI-first engineering best practices.