Sr. Software Development Engineer, AI Enablement

PitchBook PitchBook · Fintech · Seattle, WA · Enterprise Technology

Senior Software Development Engineer focused on building internal AI-powered tools and platforms to enhance developer and general productivity across PitchBook. The role emphasizes reducing friction, accelerating delivery, and embedding AI into everyday workflows, acting as a force multiplier for engineering, product, and research teams. Key responsibilities include designing and implementing AI-enabled productivity tools, leading complex initiatives, and partnering with various teams to identify high-impact AI opportunities. The role requires strong software development experience, practical experience with Generative AI/LLMs, and a focus on integrating AI into production workflows.

What you'd actually do

  1. Act as a senior technical force multiplier by building AI-powered tools, workflows, and “golden paths” that significantly accelerate delivery and reduce cognitive and operational overhead
  2. Design, implement, and iterate on internal AI-enabled productivity tools (e.g., coding assistants, research accelerators, workflow automation, decision-support tools) used by teams across the company
  3. Lead the technical design and execution of complex AI enablement initiatives, from problem discovery through production adoption
  4. Partner deeply with engineering, product, and business teams to identify high-impact opportunities where AI can meaningfully improve speed, quality, or scale
  5. Build reusable software components, libraries, and reference implementations that make AI easy, safe, and consistent to adopt

Skills

Required

  • Python
  • Generative AI and LLMs
  • integrating AI into real-world, production workflows
  • prompt engineering
  • evaluation techniques
  • responsible AI patterns
  • designing APIs, services, or libraries consumed by multiple teams
  • SQL
  • NoSQL databases
  • Git
  • CI/CD workflows
  • testing strategies

Nice to have

  • JavaScript/TypeScript
  • Java

What the JD emphasized

  • building AI-powered tools
  • internal AI-enabled productivity tools
  • AI enablement initiatives
  • AI can meaningfully improve speed, quality, or scale
  • make AI easy, safe, and consistent to adopt
  • Generative AI and LLMs
  • integrating AI into real-world, production workflows
  • prompt engineering, evaluation techniques, and responsible AI patterns

Other signals

  • designing and building AI-powered developer productivity and general productivity tools
  • reduce friction, accelerate delivery, and embed AI as a natural extension of everyday work
  • internal platforms, developer tools, workflows, and enablement patterns that help teams build, ship, and operate faster using AI
  • translate ambiguous, real-world pain points into scalable, high-impact solutions
  • lead complex initiatives end-to-end
  • raise the technical bar through strong design, implementation, and mentorship
  • influence how PitchBook teams use Generative AI, LLMs, and automation to create value