AI Systems Engineer

About the role

FTE Factory Advisors helps manufacturing and operational organizations unlock higher performance — boosting revenue, reducing costs, and driving compliance through people-first strategies. Our clients are decision-makers at the top of their industries, and they trust us to deliver lasting impact. The Opportunity 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.

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

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.

Bonus Points

• If You Have 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