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Senior Applied AI Engineer (Supply Chain)

Motorola Solutions

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