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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
Build and scale production multi-agent AI systems for enterprise clients, architecting end-to-end agentic architectures from design through operations. This role suits engineers who have shipped real AI systems into production and want to work across diverse industries and technology stacks, rather than staying within a single product company.
Our summary, not Accenture’s wording. The full posting is on their site.
Skills this role names
- CI/CD
- CrewAI
- Docker
- Helm
- Java
- Kubernetes
- LangGraph
- Microservices
- OpenAI API
- Prompt Engineering
- Python
- Retrieval-Augmented Generation (RAG)
- Serverless Computing
- Terraform
- Vector Databases
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What they ask for
Required
- Shipped multi-agent AI systems in production
- Owned evaluation harnesses and incident response for production AI systems
- Hands-on experience with agentic orchestration frameworks like LangGraph, CrewAI, or AutoGen at production depth
- Direct experience calling LLM APIs in production code
- RAG pipeline ownership including embeddings, chunking, and vector database work
- LLMOps fundamentals including eval design and prompt versioning
- Cloud-native engineering maturity with Kubernetes, Docker, microservices, serverless, and IaC
- Strong Python; Java or equivalent backend language
- Team management and people development experience
Nice to have
- Vendor-agnostic multi-LLM architecture design
- Production observability and debugging experience
- Demonstrated ability to reduce ramp-up time through reusable patterns and accelerators