Principal Applied Artificial Intelligence Engineer

Who you are

• Education: Minimum of a Bachelor of Science degree in Computer Science or a related technical/analytical discipline. (Equivalent experience is not accepted in lieu of a degree)
• Experience: 10+ years of relevant software development experience with a BS (or 8+ years of experience paired with a Master of Science in Computer Science or related field)
• Production LLM Systems: Deep hands-on experience designing and operating production LLM systems
• AI Systems Expertise: Demonstrated expertise across code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability
• AI-Augmented Development: Demonstrated experience using AI coding assistants and a strong ability to evaluate, coach others on, and selectively apply AI-generated code in a production engineering context
• Domain Expertise: Strong distributed-systems, API, security, and reliability foundations, with the ability to contribute meaningfully at a senior individual contributor level within that space
• Cross-Team Influence: Demonstrated ability to drive technical decisions and shape engineering practices beyond a single team or project scope
• Production Mastery: Proven experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment
• Communication & Alignment: Exceptional ability to communicate highly technical architectures verbally, visually, and in writing to diverse engineering audiences
• Compilers & Program Analysis: Experience with compilers, program analysis, formal or executable specifications, or legacy modernization is strongly preferred
• We value experience with enterprise platforms such as Salesforce or ServiceNow, as these skills translate well into our Enterprise-Grade Orchestration environment

What the job involves

• Appian Engineering spans the full depth of our platform: from the foundational layers that power enterprise scale, to the AI capabilities redefining what automation can do
• We operate in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. By joining our team, you will solve real-world problems that directly shape how Appian delivers our AI-Powered Process Automation platform to enterprises around the world
• As a Principal Applied AI Engineer, you will serve as the technical linchpin for applied AI on the team, bringing deep hands-on expertise in designing and operating production LLM systems and a track record of influencing engineering direction beyond your immediate scope
• Equipped with cutting-edge AI tooling, you will drive the design and delivery of high-complexity AI systems — spanning code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability — set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration
• Develop Clean Software: Architect, build, and optimize high-performance production LLM systems while maintaining a strong personal technical presence on the team
• Lead Platform Modernization: Spearhead strategic technological changes and champion code refactoring efforts to keep the core Appian codebase — and the AI systems built on it — cutting-edge, modern, and performant
• Engineer with AI: Use AI coding tools fluently as a force multiplier: generating, reviewing, and critically evaluating AI-assisted code to ship faster without compromising quality or correctness
• Lead Architecture & Delivery: Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier and AI-powered application layers — from feature scoping through implementation. Build prototypes to de-risk novel AI approaches and establish the standards others build on
• Optimize Performance & Scale: Manage product availability, latency, scalability, and efficiency by engineering deep reliability into our core software systems and performing advanced system tuning
• Drive Engineering Excellence: Radiate development best practices across the department, perform meticulous code reviews on design and implementation, and build automation frameworks to prevent problem recurrence
• Lead & Grow Engineers: Actively coach and mentor engineers at multiple levels, identify and close skill gaps on the team, and take ownership of accelerating the technical growth of those around you
• Influence Technical Documentation: Share your expert domain knowledge regularly across the department, building a reputation as a vital resource and publishing high-quality content to Engineering’s permanent documentation site