Senior Applied AI Engineer (Supply Chain)
- Chicago, United States
- Senior Level
- 5+ years
- Posted
Skills
Required
- LLMs / AI
- containerization
- Docker
- Kubernetes
- SQL
- AWS / GCP / Azure
- API
- CI/CD pipelines
- API design
- system observability tools
- software engineering / data engineering / ML engineering
- Generative AI
- Python
- Oracle
Preferred
- Conversational AI
- AI evaluation
- Langfuse
- experiment tracking
- dataset management
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, mentor junior engineers, and act as a strategic partner to supply chain leadership. Your responsibilities will include architecting and deploying robust conversational AI applications, leading the development of sophisticated agentic workflows, building event-driven data streaming pipelines, and providing technical leadership and mentorship.
Data Streaming: High proficiency with Kafka, Spark, or similar technologies to support real-time decision engines
Responsibilities
- 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
Requirements
- 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
Pay
USD 75,000 - 125,000
