Principal Applied AI Engineer
New
A
AppianAI Automation
Remote (US)Full-TimePrincipal
Salary$200,000 — $350,000 USD
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Job Details
- 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).
- Required Skills
- RESTful APIsDistributed Systems
Requirements
- Bachelor of Science degree in Computer Science or a related technical/analytical discipline (equivalent experience is not accepted in lieu of a degree).
- 10+ years of software development experience with a BS (or 8+ years with an MS in Computer Science or related field).
- Deep hands-on experience designing and operating production LLM systems.
- Demonstrated expertise across code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability.
- Experience using AI coding assistants and ability to evaluate and coach others on AI-generated code.
- Strong foundations in distributed systems, APIs, security, and reliability.
- Proven ability to drive technical decisions and influence engineering practices beyond a single team.
- Experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment.
- Exceptional verbal and written communication skills for technical architectures.
Responsibilities
- Architect, build, and optimize high-performance production LLM 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 and AI systems performant.
- Use AI coding tools fluently to generate, review, and evaluate AI-assisted code.
- Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier and AI-powered application layers.
- Manage product availability, latency, scalability, and efficiency by engineering reliability into core software systems.
- Radiate development best practices, perform meticulous code reviews, and build automation frameworks.
- Coach and mentor engineers, identify and close skill gaps, and accelerate the technical growth of team members.
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