AI Systems Engineer

FTE Factory Advisors•Detroit, MI

1d•Onsite

About The Position

We’re seeking an AI Systems Engineer to design and build the technical foundation behind our AI-enabled solutions on customer sites. This role sits at the intersection of software engineering, data engineering, and AI architecture. You’ll be responsible for turning business objectives into AI solutions that operate in production environments. You’ll serve as the technical counterpart to FTE’s manufacturing and operations experts—bringing structure, rigor, and execution discipline to AI-enabled solutions in real customer environments. You’ll own core architecture decisions, lead hands-on implementation, and develop reusable patterns as our AI delivery scales across clients and use cases.

Requirements

2+ Years of software engineering fundamentals with a bias toward clean, maintainable code (Languages such as Python, Java, R, C#, or equivalent)
Experience with AI agent frameworks, RAG architectures, and orchestration platforms (e.g., LangGraph, Haystack, or equivalent platforms)
Understanding of data modeling, data access patterns, and system integration, including hands-on experience working with enterprise relational databases and APIs (e.g., Oracle, MySQL, Microsoft SQL Server, or equivalent relational systems)
Proven ability to design for scalability, reliability, security, and long-term maintainability
Conceptual understanding of MLOps, monitoring, and operational reliability practices
Ability to operate without clean APIs or ideal data
Comfort collaborating ad communicating with non-technical stakeholders and explaining technical information clearly and concisely to stakeholders.
Strong problem-solving ability, including diagnosing system-level issues, working through incomplete or messy data, and making sound architectural tradeoffs under real-world constraints.
Self-directed, pragmatic, and focused on delivering high-quality working systems—not just ideas.

Nice To Haves

Demonstrated ability to design, build, and troubleshoot complex systems including data pipelines, APIs, distributed systems, or platform services in real-world environments
Experience working in industrial, operational, or highly regulated environments
Experience integrating solutions into existing (“brownfield”) enterprise or operational environments, including legacy systems, data sources, and vendor-managed platforms
Practical experience with MLOps, system observability, or reliability engineering in production environments
Experience with Cloud, NoSQL Databases, and Microsoft Dataverse.
Experience with enterprise and cloud native orchestration platforms (e.g., AWS Bedrock AgentCore, Microsoft Power Automate, Google Cloud Vertex, or other equivalent cloud-native platforms)
Understanding of Model Context Protocol (MCP) and/or Agent-to-Agent (A2A) emerging standards
Background designing secure enterprise data access patterns
Experience in consulting, enterprise systems, or production AI environments
Experience standardizing platforms across multiple clients or teams

Responsibilities

Serve as the technical lead for on-site AI delivery, owning solutions from concept through production deployment, ensuring they are trusted by stakeholders and designed for reuse across future engagements
Work on-site with manufacturing leaders, engineers, and operators to observe processes, and translate ambiguous business requirements into clear technical designs
Own the design and implementation of AI agents and workflows that solve real business problems and provide measurable impact
Establish prompt, retrieval, and orchestration components for AI systems
Integrate AI solutions with customer applications, APIs, and structured/unstructured data sources
Partner with Network & Security teams to design secure data access, identity, and information retrieval architectures
Implement monitoring, logging, evaluation, and reliability controls to ensure production readiness
Support internal teams by mentoring, reviewing designs, and raising the overall technical bar