1 day ago
Kochi, IndiaSenior / Staff+
Responsibilities
- Design, build, test, and deploy production-grade Generative AI, Agentic AI, Machine Learning, and LLM-powered applications on GCP using Vertex AI and Gemini.
- Develop AI agents supporting planning, reasoning, retrieval, tool calling, workflow orchestration, memory, structured outputs, and multi-step task automation.
- Build RAG solutions using embeddings, vector search, semantic search, enterprise documents, structured data, and retrieval strategies.
- Develop backend APIs, microservices, data pipelines, AI services, connectors, integration layers, and reusable agent tools.
- Integrate AI applications with GCP services, databases, enterprise applications, APIs, document repositories, and external systems.
- Implement MCP clients or servers and work with A2A patterns for tool access, agent discovery, task delegation, and multi-agent collaboration.
- Use AI orchestration frameworks such as Google ADK, LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, and CrewAI.
- Implement logging, monitoring, tracing, evaluation, observability, guardrails, security, and production support mechanisms.
- Apply software engineering practices including Git-based development, automated testing, code reviews, CI/CD, infrastructure automation, documentation, and release management.
- Provide technical guidance, perform code reviews, support junior engineers, and collaborate with architects, product owners, data engineers, backend developers, security teams, and DevOps teams.
Requirements
- 5–8 years of professional experience is required, including at least 6 years in backend development, data engineering, or a combination of both.
- 1–2 years of hands-on experience with Agentic AI, LLM application development, AI agents, RAG solutions, Generative AI workflow automation, or multi-agent systems.
- Graduation is required.
- Strong hands-on experience with Google Cloud Platform, Vertex AI, Gemini models, and Google Agent Development Kit (ADK).
- Experience developing and deploying production-grade APIs, microservices, data pipelines, AI services, cloud-native applications, or enterprise integration solutions.
- Experience with AI agents, tool calling, planning, reasoning, memory, multi-agent workflows, orchestration, MCP, A2A patterns, and enterprise integrations.
- Experience with RAG, embeddings, vector search, semantic search, chunking, document ingestion, prompt engineering, and vector databases or search platforms.
- Strong Python programming skills; Java, Node.js, or other backend technology experience is an advantage.
- Experience with databases, APIs, event-driven applications, integration layers, data ingestion, transformation, validation, metadata handling, and structured or unstructured data processing.
- Experience with scalable, secure, reliable, observable cloud workloads, system design, performance optimization, error handling, authentication, authorization, secrets management, and secure API integration.
- Experience with Git, code reviews, CI/CD pipelines, Docker, logging, and monitoring.
- Experience with AWS Bedrock, Azure AI Foundry, Azure OpenAI, Amazon SageMaker, or other AI platforms is an advantage.
- Strong analytical, troubleshooting, communication, ownership, collaboration, and technical leadership skills.
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.