Lead Agentic AI Engineer 2

We Love AI Jobs; India; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

We Love AI Jobs is seeking a Senior AI Developer specialized in Google Cloud Platform (GCP) with extensive hands-on experience in Vertex AI and Gemini. The role focuses on designing, building, and deploying production-grade Generative AI and agentic AI applications, with strong emphasis on RAG, tool calling, and enterprise integrations.

You will collaborate with AI architects, data engineers, and DevOps to deliver secure, scalable, and observable AI solutions on GCP, including API development

Qualifications

• 5+ years of professional experience in AI/ML application development, backend engineering, data engineering, or related software engineering disciplines.
• Hands-on experience with Vertex AI, Gemini models and Generative AI applications.
• Experience designing, developing, and deploying production-grade AI solutions on Google Cloud and integrating with enterprise systems.

Responsibilities

• Design, build, and deploy production-grade AI and agentic applications on Google Cloud.
• Develop intelligent AI agents capable of reasoning, retrieval, tool use, and workflow orchestration.
• Build scalable AI architectures integrating Vertex AI with GCP services (BigQuery, Cloud Run, GKE, Pub/Sub, etc.).
• Apply software engineering principles to develop secure APIs, microservices, data pipelines, and reusable AI components.

Skills

GCP

Vertex AI

Gemini

RAG

AI agents

ADK

LangChain

APIs and microservices

Education

Graduation

Tools

Google Cloud Platform (GCP)

Vertex AI

Gemini

LangChain

LangGraph

LlamaIndex

Semantic Kernel

AutoGen

Google Agent Development Kit (ADK)

Job description

# Lead Agentic AI Engineer 2Accenture Federal ServicesLocation not specifiedFull-timeAI tools:Vertex AIGeminiGoogle Agent Development Kit (ADK)LangChainLangGraphLlamaIndexSemantic KernelAutoGenUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageThis engineer builds and deploys production-grade generative AI, agentic AI, and ML applications on Google Cloud, primarily with Vertex AI and Gemini. The role spans AI agents, RAG, enterprise integrations, application quality, and production operations, working with product, data, architecture, and DevOps teams.* Permanent* On-site* 5-8 years* Graduation### Skills and expertiseGoogle Cloud Platform (GCP)Vertex AIGeminiRetrieval-Augmented Generation (RAG)AI agentsGoogle Agent Development Kit (ADK)LangChainAPIs and microservices### Key responsibilities* Design, build, and deploy production AI and agentic applications on Google Cloud.* Develop agents, RAG systems, and integrations with enterprise data and applications.* Evaluate AI solution quality and implement monitoring, tracing, guardrails, 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, agentic AI, and LLM-powered applications is the core of the role. The posting specifically calls for hands-on work with Vertex AI, Gemini, AI agents, and RAG solutions.## 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.