AI/GenAI Manager (F/H)ACCENTURE

About you

Education & Background:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Mathematics, Physics, or related field.
• 6-9 years of experience in AI, ML, or advanced analytics, including experience in consulting or client-facing environments.
• Proven experience delivering end-to-end AI or GenAI solutions in production environments.
• Experience leading teams and managing project delivery.
• Relevant certifications (Azure, AWS, GCP, ML/AI) or advanced AI/GenAI programs are a plus.

Technical Skills:

• Programming & ML: Strong experience in Python and ML frameworks (e.g.TensorFlow, PyTorch), with solid understanding of production ML systems.
• Generative AI & LLMs: Experience with RAG architectures, prompt engineering, LLM integration, and frameworks (LangChain, LlamaIndex, Semantic Kernel), including hybrid retrieval approaches (vector + graph, Graph RAG).
• Agentic AI: Familiarity with agent-based systems, including multi-agent workflows, orchestration frameworks (LangGraph, AutoGen, CrewAI), and tool-augmented reasoning.
• Knowledge Systems: Experience designing hybrid knowledge architectures combining vector databases and knowledge graphs (e.g., Neo4j, Amazon Neptune) for advanced reasoning and retrieval.
• Data & Engineering: Strong understanding of data pipelines, distributed processing (Spark), and modern data platforms (Databricks, Snowflake).
• LLMOps / AgentOps: Experience with deployment, monitoring, evaluation, and lifecycle management; familiarity with tools such as MLflow, LangSmith, or Weights & Biases.
• Cloud Platforms: Hands-on experience with Azure, AWS, or GCP, including enterprise AI services (Azure OpenAI, AWS Bedrock, Vertex AI).

Soft Skills:

• Client Engagement: Ability to interact with stakeholders and translate business needs into AI solutions.
• Communication: Strong ability to explain complex architectures to technical and non-technical audiences.
• Problem-Solving: Structured thinking and ability to navigate complex challenges.
• Leadership: Ability to lead teams, mentor junior profiles, and ensure delivery excellence.
• Adaptability: Comfortable in fast-paced environments.

Languages:

• French & English required (fluent, written and spoken)

Preferred qualifications:

• Experience delivering production-grade GenAI or agentic systems.
• Experience with agent orchestration frameworks (LangGraph, AutoGen, Semantic Kernel).
• Experience in AI governance, responsible AI, or regulatory frameworks (e.g., AI Act).
• Experience in consulting, digital transformation, or enterprise environments.
• Open-source contributions or publications in AI/GenAI.
• Advanced certifications or specialized training.

Core skills in a nutshell:

AI Strategy • Machine Learning • Generative AI & LLMs • RAG Architectures • Agentic AI • Multi-Agent Systems • Knowledge Graphs • Vector Databases • Hybrid Retrieval • LLMOps • Data Engineering • Cloud Platforms • Solution Architecture • Client Engagement • Team Leadership

What success looks like

• You deliver scalable AI and GenAI solutions that create measurable business impact.
• You successfully lead project teams and ensure high-quality delivery.
• You design robust architectures combining ML, GenAI, and agentic approaches.
• You build strong relationships with client stakeholders.
• You contribute to business development and practice growth.
• You mentor team members and strengthen team capabilities.