2 days ago
Bengaluru, IndiaSenior
Responsibilities
- Configure and develop Gemini Enterprise applications, data stores, connectors, ingestion services, and access-control behavior.
- 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 involving document parsing, chunking, embeddings, retrieval, reranking, grounding, and source attribution.
- Create custom and multi-agent workflows, enterprise automations, tool integrations, and integrations with APIs, databases, SaaS products, and business applications.
- Implement IAM, OAuth, service identities, secrets management, least-privilege access, privacy, auditability, Responsible AI, and governance controls.
- Create evaluation, quality, security, regression-testing, release, logging, tracing, monitoring, and cost-optimization processes for deployed services.
- Conduct design and code reviews, mentor engineers, document reusable patterns, and support production releases and incidents.
Requirements
- At least 7.5 years of experience, including 6 to 10 years of overall experience and 3 years in Python backend cloud integration or platform engineering.
- Hands-on Google Cloud experience with 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 LLM applications, RAG or enterprise search, document processing, embeddings, retrieval quality, grounding, structured outputs, and prompt engineering.
- Experience with tool-using LLM applications, agent orchestration, workflow state, function calling, enterprise-system integrations, IAM, SSO, OAuth, service identities, secrets, and permission testing.
- Experience with containers, CI/CD, infrastructure as code, logging, tracing, monitoring, LLMOps, evaluation pipelines, prompt and configuration management, regression testing, and production support.
- Experience collaborating with architects, product teams, security teams, and business stakeholders, mentoring engineers, and reviewing technical deliverables.
- Preferred qualifications include Gemini Enterprise or Google Agentspace implementation, Google ADK, production agent runtimes, Vertex AI Search or Discovery Engine APIs, MCP or A2A integrations, LangGraph, LangChain, multi-agent orchestration, knowledge-management or knowledge-graph solutions, Responsible AI frameworks, and relevant Google Cloud, GenAI, or AI engineering certification.
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.