Staff AI Developer

Posted 11hrs ago

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Job Description

Staff AI Developer leading scalable AI/ML architecture and production delivery at Robots and Pencils. Building reliable, secure systems for enterprise workflows and mentoring engineering teams.

Responsibilities:

  • Lead the design and implementation of complex ML/AI systems end-to-end, owning architecture decisions and driving solutions from research through production at scale
  • Build and evolve scalable ML platforms, pipelines, and infrastructure that support reliable, repeatable model development and deployment across teams
  • Set the standard for AI-forward engineering, using tools like Claude and Cursor with sophistication and helping the team adopt them effectively
  • Partner with product, engineering, and leadership to shape AI strategy and align technical direction with business outcomes
  • Translate complex AI tradeoffs, risks, and opportunities into clear narratives that drive decision-making across technical and non-technical stakeholders
  • Lead design reviews and technical discussions, raising the bar for engineering rigor and constructive challenge across the team
  • Define AI architecture and engineering standards, bringing depth on tradeoffs, long-term implications, and responsible AI practices
  • Mentor and grow junior and mid-level engineers through coaching, code reviews, and pairing on hard problems
  • Take ownership of ambiguous and high-stakes work through production, with care for reliability, cost, and safety

Requirements:

  • 7+ years professional software development experience, with 4+ years focused on AI/ML systems in production and deep hands-on experience with generative AI development
  • Expert software development background (Python or similar) with strong design sensibilities for scalable, maintainable systems
  • Deep expertise with cloud platforms, including in-depth understanding of AWS services and AWS GenAI offerings
  • Proven track record designing and shipping complex agentic systems in production environments
  • Mastery of AI frameworks and orchestration tools
  • Strong experience with evaluation frameworks and observability tools for LLM apps, including building these capabilities where they don't yet exist
  • Deep understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling
  • Extensive experience building RAG pipelines: chunking strategies, embedding models, vector databases, and advanced retrieval techniques
  • API design experience, including architecting and integrating with internal and third-party services at scale
  • Advanced cost optimization expertise: token economics, caching strategies, model routing, quantization
  • Strong working knowledge of Docker and Kubernetes for containerized deployments
  • Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude Code and Cursor