AI Systems Engineer

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 #J-18808-Ljbffr