AI Systems Engineer

Jobtailor; Illinois; On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor seeks an on-site AI delivery lead to own solutions from concept to production, collaborating with manufacturing leaders, engineers, and operators to translate business needs into robust designs. You will architect AI agents and workflows, establish orchestration components, and ensure secure data access across systems.

The role emphasizes scalable, reliable, and secure AI solutions, with strong cross-functional collaboration and mentorship.

Qualifications

• 2+ Years of software engineering fundamentals with a bias toward clean, maintainable code (Python, Java, R, C#, or equivalent).
• Experience with AI agent frameworks, RAG architectures, and orchestration platforms (e.g., LangGraph, Haystack, or equivalent).
• Understanding of data modeling, data access patterns, and system integration with relational databases and APIs (Oracle, MySQL, MS SQL Server, or equivalent).
• 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.
• Strong communication with non-technical stakeholders; clear and concise explanations.

Responsibilities

• Serve as the technical lead for on-site AI delivery from concept through production deployment.
• Work on-site with manufacturing leaders, engineers, and operators to translate business requirements into technical designs.
• Own the design and implementation of AI agents and workflows that solve real business problems and deliver measurable impact.
• Establish prompt, retrieval, and orchestration components for AI systems.
• Integrate AI solutions with customer applications, APIs, and data sources.
• Partner with Network & Security teams to design secure data access and authentication architectures.
• Implement monitoring, logging, evaluation, and reliability controls for production readiness.
• Mentor and review designs to raise the overall technical bar.

Skills

AI Solution Design

Python Programming

Data Modeling

MLOps Understanding

AI Agent Frameworks

Tools

LangGraph

Haystack

Oracle

MySQL

Microsoft SQL Server

Job description

• 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

Demonstrates expertise in AI solution design and implementation, focusing on scalability, reliability, and security while effectively collaborating with cross-functional teams and non-technical stakeholders.

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 and 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.

Core Competencies

Demonstrates expertise in AI solution design and implementation, focusing on scalability, reliability, and security while effectively collaborating with cross-functional teams and non-technical stakeholders.

Highest-signal resume keywords

• AI Solution Design
• Python Programming
• Data Modeling
• MLOps Understanding
• AI Agent Frameworks

ATS Optimization Keywords

Hard Skills

• Software Engineering Fundamentals
• Clean Code Practices
• System Integration
• Data Access Patterns
• Monitoring and Reliability Controls
• Architectural Tradeoffs
• Enterprise Relational Databases
• APIs Integration
• Orchestration Platforms
• Problem-Solving

Soft Skills

• Collaboration
• Communication
• Mentoring
• Self-Directed
• Pragmatic Approach

Industry Keywords

• AI Delivery
• Manufacturing Processes
• Stakeholder Engagement
• Technical Design
• Production Readiness

Tools & Technologies

• LangGraph
• Haystack
• Oracle
• MySQL
• Microsoft SQL Server