A
Appian
Principal ML Platform Engineer
Skills
Google Cloud PlatformDockerPythonGolangJavaMicroservicesMachine LearningAIAWSKubernetesAzure
1 month ago
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Important information
Contract type:
Permanent
Salary:
$175,000 – $325,000 / year
Location:
United States
Work mode:
Onsite
Published on:
25 September 2026
What they need
- Lead the engineering of software that matters — driving AI automation for the world’s largest enterprises
- About the Team:
- 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
- The Opportunity:
- As a Principal Software Engineer, you will serve as a technical linchpin for the team, bringing deep expertise in cloud-native architecture 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 engineering solutions, set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration
- What You’ll Do:
- Develop Clean Software: Architect, build, and optimize high-performance software 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 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 application layers — from feature scoping through implementation
- 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
- What We Equip You With:
- High-Impact Autonomy: A leadership environment where you will have real ownership over your team’s direction, the latitude to make meaningful decisions, and participation in broader Engineering discussions
- New Hire Orientation: A robust onboarding experience designed to integrate you smoothly into our technology, culture, and leadership model so you can show up for your team from day one
- Continuous Enablement: Access to premier learning resources and dedicated learning time focused on both your continued technical growth and your evolution as an engineering leader
- Sponsored Certifications: Full corporate sponsorship for professional technical certifications to advance your engineering credentials- 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
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