2 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Lead discovery, architecture, and solution-design workshops for enterprise AI use cases.
- Design end-to-end architectures for Gemini Enterprise, enterprise search, retrieval services, custom agents, models, tools, and integrations.
- Define enterprise knowledge, ingestion, indexing, retrieval, access-control, identity, and security-trimming architectures.
- Design multi-agent solutions with orchestration, tool calling, memory, planning, approvals, and human-in-the-loop controls.
- Establish responsible AI, security, risk, privacy, compliance, governance, evaluation, observability, and production-readiness standards.
- Lead LLMOps practices covering evaluation, testing, prompt and model lifecycle management, release governance, and monitoring.
- Lead and mentor engineering teams through prototyping, deployment, production support, design reviews, code reviews, security reviews, and infrastructure reviews.
- Lead client architecture discussions and contribute to proposals, estimations, demonstrations, pre-sales, and solution shaping.
Requirements
- Minimum 12 years of overall experience in enterprise technology delivery.
- Minimum 15 years of experience in Large Language Models (LLMs).
- Five years of experience in cloud solution or enterprise architecture.
- Strong Google Cloud architecture experience with practical exposure to Gemini, Vertex AI, or equivalent enterprise AI capabilities.
- Experience designing enterprise search, knowledge assistants, retrieval-augmented generation, semantic search, grounding, and agent architectures.
- Strong enterprise architecture expertise across application, integration, data, security, identity, cloud, and AI domains.
- Experience integrating enterprise platforms and data sources using APIs, connectors, event-driven architectures, data pipelines, and custom services.
- Understanding of prompt engineering, context management, model limitations, hallucination risks, evaluation, AI safety, security, and cost management.
- Preferred experience with multi-agent orchestration, MCP, A2A, ADK, agent runtimes, knowledge graphs, taxonomies, ontologies, and GenAI governance.
- Experience with enterprise AI ecosystems such as Microsoft Copilot, Azure AI, Amazon Q, OpenAI, or Anthropic is preferred; relevant cloud or AI certifications are also preferred.
Benefits
- The position is based at the Bengaluru office.
Tech Stack
Google Cloud
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.