Software Engineer - Artificial Intelligence

Introduction Join our team in the Design, Cost & Complexity (DCC) division, part of the Global Data, Insight & Analytics (GDI&A) organization. We focus on building data and AI products that enhance vehicle design efficiency, reduce costs, and simplify complexity. Collaborate with product managers, engineers, data scientists, and designers to create impactful AI-driven solutions. Required Skills & Qualifications 5 years of professional software engineering experience on product teams Proven track record of shipping software to real users and supporting it post-launch Full-stack experience: modern web front ends (e.g., React), back-end services and APIs (e.g., Node.js or Python), relational databases (e.g., PostgreSQL), and cloud platforms (e.g., GCP) Solid data modeling and API design skills Hands-on use of AI coding tools, with interest or experience in building LLM-based features Good engineering practices: automated testing, CI/CD, code review, and security awareness Clear communication with engineers, product partners, and business users A bias for action and the ability to learn new domains quickly Prior work experience at client or in client's industry Applicants must be able to work directly for Artech on W2 Preferred Skills & Qualifications Bachelor's degree in computer science, engineering, or a related field, or equivalent experience Experience with agent frameworks, MCP, retrieval-augmented generation, or LLM evaluation Experience building tools for engineers (e.g., design, simulation, test, calibration, PLM, or manufacturing) Automotive or manufacturing domain experience Experience working with distributed or vendor teams Day-to-Day Responsibilities Build and ship features end to end across front end, back end, and data layers, then release and support them in production Help turn working prototypes into secure, reliable, maintainable software Propose designs, weigh trade-offs, and help shape data models, APIs, and integrations Use AI coding tools daily, and build AI features with guardrails, evaluation, and human oversight Connect our products to the tools and data engineers already use, including legacy systems Write automated tests, review pull requests, and follow good practices for security, CI/CD, and observability Spend time with the engineers who use our products and use what you learn to improve them Share knowledge, pair with teammates, and help newer engineers, including vendor engineers on our team Flag technical debt, risks, and quality concerns early, with options to fix them For immediate consideration please click APPLY to begin the screening process with Alex.