Principal ML Platform Engineer

About the role

Join Appian, a leading provider of AI-Powered Process Automation. As a Principal ML Platform Engineer, you will lead the engineering of software that drives AI automation for the world's largest enterprises. You will work in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. Your responsibilities will include developing clean software, leading platform modernization, engineering with AI, optimizing performance and scale, driving engineering excellence, and mentoring other engineers. You will have the opportunity to make a significant impact on the direction of the team and the company as a whole. Key missions: Architect, build, and optimize high-performance software systems while maintaining a strong personal technical presence on the team.. Spearhead strategic technological changes and champion code refactoring efforts to keep the core Appian codebase cutting-edge, modern, and performant.. Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier application layers — from feature scoping through implementation. Profile: - Cross-Team Influence: Demonstrated ability to drive technical decisions and shape engineering practices beyond a single team or project scope - 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) - 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 - 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) - Communication & Alignment: Exceptional ability to communicate highly technical architectures verbally, visually, and in writing to diverse engineering audiences - Domain Expertise: Deep working knowledge of distributed systems, cloud infrastructure, and the ability to contribute meaningfully at a senior individual contributor level within that space - Production Mastery: Proven experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment - Technical Mastery: Expert coding, scripting, and debugging proficiency in one or more core enterprise programming languages, specifically Java, Python, or Go - Cloud Platforms: Deep experience developing and operating infrastructure across public cloud ecosystems, specifically AWS, Azure, and/or GCP - We value experience with enterprise platforms such as Salesforce or ServiceNow, as these skills translate well into our Enterprise-Grade Orchestration environment - Cloud Architecture: Strong experience designing microservices, working with containerization (Docker, Kubernetes), and implementing modern CI/CD pipelines