Senior Software Engineer, Fde

Handshake · Enterprise · San Francisco, CA · Engineering

Senior Forward Deployed Engineer to serve as a technical leader at the intersection of engineering and strategic customers (leading AI labs). Owns end-to-end lifecycle of high-impact deployments, architecting, building, and scaling solutions to improve customer workflows and model performance. Operates across the stack in ambiguous, fast-changing environments.

What you'd actually do

  1. Partner with AI labs and cross-functional stakeholders to deeply understand technical challenges, translate ambiguous requirements into actionable engineering plans, and drive alignment across teams.
  2. Own the design, architecture, and delivery of tailored, production-grade solutions for complex, high-impact customer needs—often with minimal precedent or existing playbooks.
  3. Mentor and uplevel other engineers through code reviews, architectural guidance, and establishing best practices for forward-deployed work.
  4. Make key architectural decisions around reliability, scalability, and security, and set the technical direction for repeatable deployment patterns.
  5. Rapidly prototype, test, and iterate on tools in response to real-time feedback, balancing speed of delivery with long-term maintainability.

Skills

Required

  • 5+ years of professional software engineering experience
  • meaningful time spent in customer-facing, solutions-oriented, or forward-deployed roles
  • Strong proficiency with ReactJS and TypeScript
  • high bar for code quality, usability, and accessibility
  • Deep understanding of relational databases (e.g., PostgreSQL)
  • data modeling
  • system design
  • Experience with cloud infrastructure (AWS, GCP)
  • deployment pipelines
  • production operations at scale
  • Demonstrated ability to lead technical projects end-to-end in ambiguous environments with shifting requirements
  • Excellent communication and stakeholder management skills
  • build trust with both technical and non-technical audiences
  • Track record of mentoring engineers and raising the bar on engineering practices within a team

Nice to have

  • Experience architecting and delivering production systems for LLMs or other AI-powered products in real-world, customer-facing environments
  • Background in building or contributing to component libraries, design systems, or reusable deployment frameworks
  • Proven experience with performance optimization and scaling of full-stack applications under real-world constraints and high-traffic conditions
  • Prior experience in a forward-deployed, solutions engineering, or technical consulting role at a high-growth company

What the JD emphasized

  • high-impact deployments
  • complex technical requirements
  • ambiguous environments
  • high-impact customer needs
  • minimal precedent or existing playbooks
  • ambiguous environments with shifting requirements

Other signals

  • Works directly with frontier AI lab researchers
  • Supports all of the frontier AI labs, working on their most complex data at the largest scale
  • Own the end-to-end lifecycle of high-impact deployments—from scoping complex technical requirements to architecting, building, and scaling solutions that directly improve customer workflows and model performance.