Lead Agentic AI Engineer

We Love AI Jobs; Ernakulam, Thiruvananthapuram, Coimbatore District; On-site; INR 2,800,000 - 4,200,000; Full time

Job summary

Accenture Federal Services in Kochi, Kerala seeks a Lead AI Engineer with 5+ years in AI/ML to design and deploy production-grade Generative AI and Agentic AI on Google Cloud, using Vertex AI and Gemini models. You will develop AI agents, RAG solutions, and enterprise integrations, ensuring secure, scalable, and observable deployments.

The role emphasizes tool calling, orchestration, and multi-agent collaboration with a focus on delivering reliable AI services for enterprise customers.

Qualifications

• 5+ years of professional experience in AI/ML application development or related software engineering disciplines.
• Strong hands-on experience with Vertex AI and Gemini models.
• Proficient in building AI applications, agents, and RAG solutions for enterprise systems.
• Experience with APIs, microservices, and cloud-native architectures.
• Knowledge of tool calling, orchestration, memory management, and multi-agent patterns is desirable.

Responsibilities

• Design, build, and deploy production-grade Generative AI, Agentic AI, and LLM-powered applications on Google Cloud, primarily using Vertex AI and Gemini models.
• Develop AI agents capable of reasoning, retrieval, tool use, orchestration, and enterprise integrations.
• Implement monitoring, security, guardrails, and cost-efficient production support for AI solutions.
• Collaborate with AI architects, data engineers, product teams, and DevOps to deliver scalable, observable systems.

Skills

GCP

Vertex AI

Gemini models

RAG

APIs & microservices

LangChain

LangGraph

LlamaIndex

Semantic Kernel

AutoGen

CrewAI

Education

Graduation

Tools

BigQuery

Cloud Storage

Cloud Run

GKE

Pub/Sub

API Management

Job description

# Lead Agentic AI EngineerAccenture Federal ServicesLocation not specifiedFull-timeAI tools:Vertex AIGeminiLangChainLangGraphLlamaIndexSemantic KernelAutoGenCrewAIUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageThis role develops and deploys generative AI, agentic AI, and LLM applications on Google Cloud, primarily using Vertex AI and Gemini models. You will build agents and RAG solutions, integrate them with enterprise systems, and assess their quality, reliability, security, and cost.* Full-time* On-site* 5–8 years* Graduation### Skills and expertiseGoogle Cloud PlatformVertex AIGeminiRAGAI agentsAPIs and microservicesMCPLangChain### Key responsibilities* Build and deploy generative AI and agentic applications using Vertex AI and Gemini models.* Develop AI agents and RAG solutions with retrieval, tool use, orchestration, and enterprise integrations.* Evaluate AI quality and implement monitoring, tracing, guardrails, security, and production support.## How this job comparesCompared with 57 open lead machine learning jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 57 open lead machine learning jobs at 36 companies.Remote work: This job is on site. 12 of the 57 lead machine learning jobs (21%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. Building and deploying generative AI, LLM, and agentic applications is the central work of the role. The posting specifically calls for hands-on use of Vertex AI, Gemini models, RAG, and AI agents.## Full descriptionJob Title - Lead AI Engineer – Specialist - ACS SONGManagement Level: Level 9 - SpecialistLocation: Kochi, Coimbatore, TrivandrumMust have skills: GCP, Generative AIGood to have skills: AWS Bedrock/ Azure AI Foundry/ Azure OpenAI / Amazon SageMaker or other AI platformExperience: 5 -8 years of experience is requiredEducational Qualification: GraduationJob SummaryWe are seeking a Senior AI Developer / Engineer specializing in Google Cloud Platform (GCP) with 5+ years of professional experience in AI/ML application development, backend engineering, data engineering, or related software engineering disciplines. The role will focus on designing, developing, and deploying production-grade Generative AI, Agentic AI, Machine Learning, and LLM-powered applications using Google Cloud technologies, with Vertex AI as the primary AI platform.The ideal candidate should have strong hands-on experience with Vertex AI, Gemini models, Generative AI applications, RAG, AI agents, APIs, cloud-native application development, and enterprise integrations. Experience with Agentic AI concepts such as tool calling, orchestration, memory, MCP, A2A, and multi-agent systems is highly desirable.The candidate will work closely with AI architects, data engineers, application developers, product teams, and DevOps engineers to build scalable, secure, observable, cost-efficient, and production-ready AI solutions. Experience with equivalent AI platforms such as AWS Bedrock or Azure AI Foundry is considered an additional advantage.Roles and Responsibilities• Design, build, and deploy production-grade AI, Generative AI, and Agentic AI applications on Google Cloud, primarily using Vertex AI and Gemini models.• Develop intelligent AI applications and agents capable of reasoning, retrieval, tool use, workflow orchestration, structured output generation, task automation, and enterprise system integration.• Build scalable AI application architectures integrating Vertex AI with GCP services such as BigQuery, Cloud Storage, Cloud Run, GKE, Pub/Sub, API management, databases, and enterprise applications.• Apply strong software engineering principles to develop secure APIs, microservices, AI services, data pipelines, agent tools, and reusable AI components suitable for enterprise production environments.• Design, develop, test, and deploy Generative AI, LLM, Machine Learning, and Agentic AI solutions using Google Cloud Platform and Vertex AI.• Build applications using Vertex AI, Gemini models, Vertex AI APIs, embeddings, model endpoints, prompt management, grounding, function/tool calling, and other GCP AI capabilities.• Develop AI agents capable of planning, reasoning, tool calling, information retrieval, workflow execution, memory management, and multi-step task automation.• Design and implement Retrieval-Augmented Generation (RAG) solutions using Vertex AI, embeddings, vector search, enterprise documents, structured data, semantic search, and appropriate retrieval strategies.• Build integrations between AI applications and GCP services such as BigQuery, Cloud Storage, Cloud Run, Cloud Functions, GKE, Pub/Sub, Secret Manager, and other cloud-native services.• Develop backend APIs, microservices, connectors, integration services, and reusable tools that allow AI applications and agents to interact securely with enterprise systems, databases, APIs, and external services.• Implement Model Context Protocol (MCP) clients or servers where applicable to provide standardized and secure access to tools, APIs, enterprise applications, and data sources.• Work with Agent2Agent (A2A) patterns or protocols for agent discovery, task delegation, inter-agent communication, and multi-agent collaboration where required.• Work with AI/LLM orchestration frameworks such as Google Agent Development Kit (ADK), LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or equivalent technologies.• Evaluate and improve AI application quality across accuracy, groundedness, hallucination reduction, prompt quality, retrieval quality, latency, reliability, scalability, security, and cost efficiency.• Implement logging, monitoring, tracing, observability, evaluation, guardrails, and production support mechanisms for AI applications and agentic workflows.