2 days ago
Bengaluru, IndiaSenior
Responsibilities
- Configure and develop Gemini Enterprise applications, data stores, connectors, and custom ingestion services.
- Build Python services, APIs, Gemini and Vertex AI integrations, and tool-using or multi-agent workflows.
- Develop and tune RAG pipelines covering document processing, embeddings, retrieval, reranking, grounding, and source attribution.
- Integrate enterprise APIs, databases, SaaS products, and business applications using secure authentication, permissions, validation, retries, and timeouts.
- Implement IAM, OAuth, service identities, secrets management, least-privilege access, privacy, auditability, and Responsible AI controls.
- Create automated and human evaluation approaches for grounding, relevance, safety, hallucination management, agent effectiveness, and task completion.
- Maintain automated tests, CI/CD, infrastructure as code, configuration and prompt versioning, release controls, logging, tracing, monitoring, and production support.
- Conduct design and code reviews, mentor engineers, and create reusable patterns, templates, documentation, and reference implementations.
Requirements
- Minimum 5 years of experience is required, with 6–10 years of overall experience including 3 years in Python backend cloud integration or platform engineering.
- At least 7.5 years of experience with Large Language Models is stated as an additional requirement.
- Hands-on Google Cloud experience, including Gemini or Vertex AI APIs and application hosting such as Cloud Run or an agent runtime.
- Practical experience implementing enterprise AI, search, knowledge-assistant, copilot, or agent solutions.
- Strong Python and API development skills with working knowledge of SQL, JSON, Git, automated testing, error handling, and maintainable service design.
- Experience with RAG or enterprise search, document processing, embeddings, retrieval quality, grounding, structured outputs, prompt engineering, and tool-using LLM applications.
- Working knowledge of IAM, SSO, OAuth, service identities, secrets, source-level permissions, containers, CI/CD, infrastructure as code, logging, tracing, monitoring, and LLMOps.
- Experience mentoring engineers, reviewing technical deliverables, troubleshooting production systems, and collaborating with architects, product, security, and business teams.
- Preferred experience includes Gemini Enterprise or Google Agentspace, Google ADK, production agent runtimes, Vertex AI Search or Discovery Engine APIs, MCP, A2A, LangGraph, LangChain, multi-agent orchestration, knowledge graphs, and GenAI evaluation or governance frameworks.
- Relevant Google Cloud, GenAI, or AI engineering certification is preferred.
Benefits
- The position is based at the Bengaluru office.
- The role includes work with geographically distributed delivery teams and cross-functional architects, product, security, and business stakeholders.
Categories
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.