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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
This role involves leading the design and delivery of advanced AI solutions—from machine learning and generative AI to multi-agent systems—for enterprise clients, combining technical architecture decisions with team leadership and client engagement. The ideal candidate brings hands-on experience building production AI systems at scale, the ability to translate business problems into robust implementations, and a track record of managing technical teams through complex, end-to-end projects.
Our summary, not Accenture’s wording. The full posting is on their site.
Skills this role names
- Amazon Web Services (AWS)
- Apache Spark
- CrewAI
- Databricks
- LangChain
- LangGraph
- LlamaIndex
- Microsoft Azure
- MLflow
- Neo4j
- Prompt Engineering
- Python
- PyTorch
- Retrieval-Augmented Generation (RAG)
- Semantic Kernel
- Snowflake
- TensorFlow
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What they ask for
Required
- Degree in computer science, data science, machine learning, mathematics, physics or related field
- Proven experience implementing end-to-end AI or GenAI solutions in production
- Experience managing teams and delivering projects
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch)
- Experience with RAG architectures, prompt engineering, and LLM integration
- Knowledge of multi-agent systems and orchestration frameworks
- Experience with hybrid knowledge systems combining vector stores and knowledge graphs
- Expertise in data pipelines, distributed processing, and modern data platforms
- Experience with LLMOps: deployment, monitoring, evaluation, and lifecycle management
- Practical experience with Azure, AWS, or GCP including AI services
- Fluent French and English (written and spoken)
Nice to have
- Production experience with GenAI or agentic systems
- Experience with agent orchestration frameworks (LangGraph, AutoGen, Semantic Kernel)
- Background in AI governance, responsible AI, or regulatory compliance (e.g. AI Act)
- Consulting or digital transformation experience with enterprise clients
- Open-source contributions or publications in AI/GenAI
- Advanced certifications or specialized training
- Cloud certifications (Azure, AWS, GCP) or ML/AI certifications