Job Summary
Role SummaryWe are seeking an experienced Agentic AI Engineer to design, build, deploy, and optimize enterprise-grade AI agents and multi-agent ecosystems. The ideal candidate should have hands-on expertise in Agent Development Kit (ADK), LangChain/LangGraph, Multi-Agent Orchestration, RAG architectures, Vector Databases, LLM tuning, and Gemini Enterprise platforms, with proven experience deploying AI solutions into production environments. The role aligns with enterprise AI architectures and production-grade agentic platforms highlighted in internal AI initiatives. 123Key ResponsibilitiesDesign and develop autonomous AI agents and multi-agent systems using ADK, LangChain, LangGraph, CrewAI, AutoGen, and related frameworks. 124Build enterprise-grade RAG solutions integrating vector databases, semantic retrieval, grounding, and knowledge management. 14Architect multi-agent orchestration patterns including planning, reasoning, memory, tool-calling, and workflow execution. 14Develop and optimize prompt engineering, agent memory, and contextual reasoning capabilities.Fine-tune, evaluate, and optimize LLMs for enterprise use cases.Design and implement agent observability, monitoring, guardrails, governance, and security controls. 32Integrate AI agents with enterprise systems including APIs, databases, SharePoint, Salesforce, CRM, ERP, and business applications. 43Deploy and operate AI platforms on cloud environments (GCP, Azure, AWS) with MLOps and CI/CD best practices.Lead production deployments, troubleshooting, model monitoring, and continuous optimization.
Key Responsibilities
Role SummaryThe Agentic AI Solution Lead will partner with business, product, and technology teams to identify opportunities for AI-led transformation through intelligent agents and autonomous workflows. The role requires expertise in translating business requirements into scalable Agentic AI solutions leveraging Gemini Enterprise, ADK, RAG, and multi-agent architectures. Enterprise deployments and AI transformation experience are essential. 34Key Functional ResponsibilitiesEngage stakeholders to identify AI automation opportunities and business use cases.Define Agentic AI strategy, roadmaps, and implementation plans.Conduct discovery workshops and solution design sessions.Translate business requirements into agent workflows and multi-agent architectures.Drive adoption of Gemini Enterprise, GE Agent Platform, and enterprise AI ecosystems. 43Define AI governance, compliance, risk, and Responsible AI standards.Work with engineering teams to ensure production readiness and deployment excellence.Create reusable frameworks, accelerators, and solution blueprints.Lead PoCs, MVPs, and enterprise-scale rollouts.Establish KPI frameworks for measuring agent effectiveness and business ROI.Support pre-sales, client presentations, solution demonstrations, and technical proposals.Mentor teams on Agentic AI best practices and emerging technologies.Functional CompetenciesAI Strategy & Roadmap DefinitionBusiness Process TransformationEnterprise Solution ArchitectureStakeholder ManagementAI Governance & CompliancePresales & ConsultingProduct ThinkingChange ManagementAgile DeliveryProgram Leadership
Skill Requirements
Agentic AI, Agent Development, Multi Agent Orchestration, Google ADK, Langchain, Vector Databases, RAG, LLM Tuning, Gemini Enterprise, GE Agent Platform, experience of deploying AI agents in production environments
Required Technical SkillsAgentic AI & GenAIAgentic AI ArchitectureAI Agent DevelopmentMulti-Agent SystemsAgent OrchestrationAgent Memory & State ManagementTool Calling / Function CallingMCP (Model Context Protocol)Frameworks & PlatformsGoogle ADK (Agent Development Kit)LangChainLangGraphCrewAI / AutoGenGemini EnterpriseGE Agent Platform / Enterprise Agent PlatformsVertex AI Agent EngineLLM & RAGRetrieval-Augmented Generation (RAG)Embedding ModelsPrompt EngineeringContext EngineeringLLM Fine-TuningModel Evaluation FrameworksHallucination MitigationVector DatabasesPineconeFAISSChromaPGVectorWeaviateMilvusCloud & DeploymentGCP (Preferred)Azure/OpenAIAWSDockerKubernetesCI/CD PipelinesMLOps & AgentOpsProgrammingPython (Mandatory)FastAPIREST APIsSQL/NoSQL Databases
Other Requirements
Experience building production AI assistants and autonomous workflows.Experience with enterprise governance, compliance, security, and Responsible AI.Relevant certifications in Google Cloud, Gemini, GenAI, or AI Engineering.
Proven experience deploying AI agents to production and managing enterprise adoption.Experience handling multi-disciplinary teams, client-facing engagements, and transformation programs.