AI Engineer (Supply Chain)

Supply Chain Agents: Develop modular, multi-agent systems using ATLAS AI that leverage tool-use, skills, memory, and multi-step reasoning (Chain-of-Thought) to interact with the CDF Knowledge Graph for solving supply chain problems. This should be product-ready and handed to the product and delivery organisation.Knowledge Graph Orchestration: Design and build precise, reliable tools that can query and traverse the supply chain knowledge graph, handling complex relationships, multi-hop lookups, and returning accurate structured data. The supply chain agents should be able to reason over it.Domain-Specific Reasoning: Craft advanced prompt chains and evaluation frameworks to ensure agents provide accurate, operationally safe recommendations for industrial use cases.Rapid development and deployment: Operates with high autonomy and minimal guidance to build functional prototypes directly on customer data or synthetic data, test with customers and SMEs and support integration with customers working along with a value-delivery team.

5-8 years in AI/ML Engineering: Proven track record of delivering production-grade AI features. Hands-on experience with LLMs, embeddings, prompt engineering, and related techniques.Advanced Agent Frameworks: Experience building LLM-driven or agentic systems (e. g., using LangChain or similar frameworks).Knowledge Graph Proficiency: Ability to query and navigate complex relational and graph data models. You should be comfortable thinking in "nodes and edges".You're a strong full-stack engineer: You can work across the stack and own delivery of functional, user-facing solutions: Frontend: React (or similar) + TypeScript, Backend: Python, Kotlin, or similar for orchestration and API integration.Industrial and Supply Chain Data Literacy: Deep understanding of how to work with "imperfect" industrial data and cross-functional supply chain data, including time series and sparse metadata.Autonomous Maker Mindset: A "show, don't tell" approach. Bias towards rapid iteration. You can take a schema (like the Integrated Supply Chain model) and independently identify how to build an agent that provides value from it.Familiarity with AI-powered IDEs: Experience using coding assistants (Cursor, Claude Code, Copilot, or similar) and comfortable using LLMs to accelerate development, debugging, and documentation tasks.You communicate clearly: Strong storytelling skills for both technical and executive audiences.You write quality code: Clean, maintainable, and scalable with solid practices around testing, version control, and code review. Bonus .