Senior Applied AI Engineer, Supply Chain

Motorola Solutions

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Chicago, IL
Salary
$75,000–$125,000 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $185k
This role $100k
$57k most similar roles pay here $243k

This role pays less than 99% of similar roles. Most pay $149,500–$219,675 — the shaded band above. At the midpoint, this role pays about $100k versus about $185k for comparable roles.

Based on 240 similar postings.

Employer

About Motorola Solutions

Motorola Solutions, Inc. (NYSE: MSI) is a leading American technology company providing mission-critical communications, video security, and analytics for public safety and enterprise customers.

Motorola Solutions currently has 157 open roles on FindRole.

Listed pay typically runs $100,000–$133,000 across 123 roles with salary data.

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View all roles at Motorola Solutions

At a glance

TL;DR · Senior Applied AI Engineer, Supply Chain

As a Senior Applied AI Engineer on the Supply Chain team, you will drive the technical vision and architectural design for integrating foundational models and autonomous systems into a global logistics network. You will own the end-to-end lifecycle of enterprise-grade AI products, evolving conversational interfaces into multi-agent systems that execute real-time supply chain decisions. Your daily work involves architecting secure LLM deployments, designing evaluation frameworks, and building event-driven data streaming pipelines to detect anomalies. You will utilize Python, SQL, AWS Bedrock, Langfuse, and orchestration frameworks like LangGraph, CrewAI, or AutoGen. Additionally, you will manage vector databases, Docker, and Kubernetes while integrating with ERP systems and BI platforms. This role solves complex logistical challenges by transforming manual processes into proactive, automated solutions within the supply chain domain to improve operational resilience and efficiency.

What you'll do

  • Architect and deploy scalable LLM applications with low latency and high accuracy using proprietary ERP and warehouse data.
  • Develop multi-agent systems capable of executing autonomous supply chain actions like generating purchase orders and rerouting freight.
  • Build event-driven data streaming pipelines to detect and alert on supply chain anomalies in real time.
  • Manage the transition and evaluation of agentic orchestration frameworks such as LangGraph, CrewAI, or AutoGen.
  • Design comprehensive AI evaluation strategies and benchmarking systems using tools like Langfuse for continuous model improvement.
  • Integrate AI agents with underlying data warehouses, BI platforms, and operational APIs to automate business workflows.
  • Mentor junior engineers and establish MLOps standards, coding practices, and architectural reviews for the team.
  • Translate complex supply chain bottlenecks into technical architectures and automated solutions for business leadership.

What we're looking for

  • Bachelor's Degree in Computer Science, Artificial Intelligence, or a related field.
  • 5+ years of software engineering, data engineering, or ML engineering experience.
  • Proven track record of architecting and deploying LLMs or AI agents into production environments.
  • Expert-level proficiency in Python and SQL.
  • Deep understanding of distributed systems, microservices, and cloud infrastructure (AWS/GCP/Azure).
  • Mastery of LLM orchestration frameworks, vector databases, and retrieval optimization techniques.
  • Experience with containerization (Docker, Kubernetes), CI/CD pipelines, and API design.
  • Knowledge of ETL/ELT pipelines and experience with BI automation or Text-to-SQL workflows.
  • Deep working knowledge of enterprise supply chain dynamics and ERP architecture (preferred).
  • Experience building custom evaluation frameworks or fine-tuning open-source foundation models (preferred).
  • High proficiency with Kafka, Spark, or similar technologies for real-time decision engines (preferred).

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