Staff AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Direct the design and execution of intricate ML/AI systems from start to finish, taking ownership of architectural decisions and steering solutions from research to large-scale production.

• Develop and enhance scalable ML platforms, pipelines, and infrastructure that facilitate reliable and repeatable model development and deployment across various teams.

• Establish benchmarks for AI-driven engineering, employing tools like Claude and Cursor with expertise and assisting the team in their effective adoption.

• Collaborate with product, engineering, and leadership to formulate AI strategies and ensure that technical directions align with business objectives.

• Convert complex AI trade-offs, risks, and opportunities into clear narratives that guide decision-making among both technical and non-technical stakeholders.

• Facilitate design reviews and technical discussions, elevating the standards for engineering rigor and fostering constructive challenges within the team.

• Define AI architecture and engineering standards, providing insights on trade-offs, long-term implications, and responsible AI practices.

• Mentor and nurture junior and mid-level engineers, amplifying impact through coaching, code reviews, and collaborative problem-solving.

• Assume responsibility for the most ambiguous and high-stakes tasks, guiding them to production while considering reliability, cost, and safety.

⛳️ Requirements

• Over 7 years of professional software engineering experience, with more than 4 years dedicated to AI/ML systems in production and substantial hands-on expertise in generative AI development.

• Strong software engineering foundation (Python or similar) with excellent design sensibilities for scalable and maintainable systems.

• In-depth knowledge of cloud platforms, particularly a comprehensive understanding of AWS services and AWS GenAI offerings.

• Proven history of designing and deploying complex agentic systems in production settings.

• Mastery of AI frameworks and orchestration tools.

• Extensive experience with evaluation frameworks and observability tools for LLM applications, including developing these capabilities where they are not yet available.

• Profound understanding of AI safety, responsible AI principles, prompt injection defenses, and handling of PII.

• Significant experience in building RAG pipelines: chunking strategies, embedding models, vector databases, and advanced retrieval techniques.

• Experience in API design, including the architecture and integration of internal and third-party services at scale.

• Advanced knowledge in cost optimization: token economics, caching strategies, model routing, and quantization.

• Proficient working knowledge of Docker and Kubernetes for containerized deployments.

• Proven, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude Code and Cursor.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off

• Remote work options