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Listed on Accenture’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
You will architect and deploy multi-agent AI systems in production enterprise environments, working directly with client engineering teams and setting standards for RAG pipelines, LLM integration, and observability across the practice. This role combines senior technical leadership with hands-on ownership of agentic systems that run inside real organizations, not prototypes.
Our summary, not Accenture’s wording. The full posting is on their site.
Skills this role names
- CrewAI
- Docker
- Helm
- Java
- Kubernetes
- LangGraph
- OpenAI API
- Prompt Engineering
- Python
- Retrieval-Augmented Generation (RAG)
- Terraform
- Vector Databases
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What they ask for
Required
- Minimum 1 year shipping production agentic AI systems
- Hands-on experience with agentic orchestration frameworks at production depth
- Direct experience calling LLM APIs in production code
- RAG pipeline ownership including embeddings and chunking strategy
- LLMOps fundamentals including eval harness design and prompt versioning
- Cloud-native engineering with Kubernetes, Docker, microservices, CI/CD, and IaC
- Strong Python or equivalent backend language with production debugging experience
- Experience managing and developing engineering teams
Nice to have
- Multiple production agentic system deployments
- Multi-agent orchestration across complex enterprise environments
- Vendor-agnostic LLM architecture patterns
- Experience with multiple LLM providers and cost governance
- Published reusable patterns or accelerators at scale