Senior Applied AI Engineer (Supply Chain)

Join our Supply Chain team as a Senior Applied AI Engineer. You will drive the technical vision and architectural design for integrating foundational models and autonomous systems into our global logistics network. You will own the end-to-end lifecycle of enterprise-grade AI products, architect secure and scalable LLM deployments, and mentor junior engineers. You will also act as a strategic partner to supply chain leadership, translating operational bottlenecks into deployed AI solutions.

• Architect, deploy, and scale robust Conversational AI applications, ensuring low latency, high accuracy, and strict data governance.
• Lead the development of sophisticated agentic workflows capable of taking independent action, including auto-generating purchase orders and dynamically rerouting freight.
• Design end-to-end AI evaluation strategies, leveraging Langfuse for experiment tracking and dataset management to run systematic benchmarks and drive continuous model improvements.

• Communication: Proven ability to influence product roadmaps, manage technical debt, and communicate complex AI constraints and capabilities to non-technical business leaders
• Production Engineering: Extensive experience with containerization (Docker, Kubernetes), CI/CD pipelines, API design, and system observability tools
• Experience: 5+ years of software engineering, data engineering, or ML engineering experience, with a proven track record of architecting and deploying LLMs or AI agents into production environments
• Generative AI Expertise: Mastery of LLM orchestration frameworks (LangChain, LangGraph, AutoGen, CrewAI), vector databases (e.g., Pinecone, Weaviate), and retrieval optimization techniques (hybrid search, semantic routing)
• Programming & Systems: Expert-level Python and SQL. Deep understanding of distributed systems, microservices, and modern cloud infrastructure (AWS/GCP/Azure)
• Infrastructure: Knowledge of containerization (Docker, Kubernetes) and cloud-native architecture on AWS
• Data & Integration: Experience with BI automation, Text-to-SQL workflows, and programmatically generating visualizations or dashboards via API (e.g., Power BI, Tableau, Looker, custom frameworks). Familiarity with ETL/ELT pipelines and SQL
• Domain Expertise: Deep working knowledge of enterprise supply chain dynamics, ERP architecture (e.g., SAP, Oracle), procurement, or logistics optimization
• Advanced AI Tooling: Experience building custom evaluation frameworks (e.g., Ragas) or fine-tuning open-source foundation models for domain-specific tasks
• Data Streaming: High proficiency with Kafka, Spark, or similar technologies to support real-time decision engines