2 days ago
Bengaluru, IndiaSenior
Responsibilities
- Configure and develop Gemini Enterprise applications, data stores, connectors, and custom ingestion services.
- Build Python services, Gemini and Vertex AI integrations, and tool-using agents with prompts, structured outputs, workflow state, approvals, and human-in-the-loop controls.
- Develop and tune RAG pipelines covering document parsing, chunking, 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, secrets management, least-privilege access, auditability, privacy, and Responsible AI controls.
- Create evaluation, quality, security, regression, monitoring, logging, tracing, and production-support processes.
- Conduct design and code reviews, mentor engineers, and create reusable patterns, templates, documentation, and reference implementations.
Requirements
- At least 3 years of experience is stated, with 6 to 10 years of overall experience including 3 years in Python backend cloud integration or platform engineering.
- At least 7.5 years of experience in Large Language Models is additionally stated.
- Hands-on Google Cloud experience, including Gemini or Vertex AI APIs and application hosting such as Cloud Run or an agent runtime.
- Strong Python and API development skills with working knowledge of SQL, JSON, Git, automated testing, error handling, and maintainable service design.
- Practical experience implementing RAG or enterprise search and understanding document processing, embeddings, retrieval quality, grounding, structured outputs, and prompt engineering.
- Experience with tool-using LLM applications, agent orchestration, workflow state, function calling, enterprise integrations, IAM, SSO, OAuth, service identities, and secrets.
- Experience with containers, infrastructure as code, logging, tracing, monitoring, evaluation pipelines, prompt and configuration management, regression testing, and production operations.
- Preferred qualifications include Gemini Enterprise or Google Agentspace experience, Google ADK, Vertex AI Search or Discovery Engine APIs, MCP or A2A integrations, LangGraph, LangChain, multi-agent orchestration, knowledge graphs, GenAI evaluation and governance, and relevant Google Cloud or AI certifications.
- Experience mentoring engineers, reviewing technical deliverables, troubleshooting, and collaborating with architects, product, security, and business teams.
Benefits
- The position is based at the employer's Bengaluru office.
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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.