Senior Director, Software Development, Test Automation
Lila Sciences · San Francisco, CA USA · San Francisco, CA
CHECKED 15H AGO
Bio & Science AIonsitedirector$300k–$390k
At a glance
Highlights
- Architect and ship the test automation platform adopted org-wide by default.
- Drive AI-driven test generation and eval discipline for AI agent stack.
- Build QC validation framework for autonomous lab execution and science ops.
What they offer
- Competitive base compensation with bonus potential and early-stage equity
- Medical, dental, and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with company-wide holidays
- Paid parental leave
- Educational assistance program
- Commuter benefits and company-subsidized lunch
Ideal candidate
Builder-leader with deep quality engineering instincts who scales through platform leverage and influence. Customer- and UX-obsessed, metrics-driven, and excited by AI-powered science and autonomous labs.
Requirements
- 10+ years in software engineering, with 5+ years leading test automation, quality engineering, or platform/SRE-adjacent functions
- 3+ years managing engineers, including building or scaling a team
- Strong software architect with hands-on Python and/or TypeScript expertise
- Deep CI/CD expertise at scale including monorepo orchestration, parallelization, caching and flake management
- Demonstrated build-vs-buy judgment for test infra and tooling with TCO trade-offs
- Hands-on AI-driven test automation using LLMs with rigorous eval validation
- Track record of standing up an adopted test automation platform
- Working knowledge of Google SRE practices applied to pre-production quality
- Metrics-driven leader who scales through platform leverage and influence
- Customer- and UX-first instincts for test automation
Lab profile
About Lila Sciences
Building an autonomous science platform where AI, automation, and biology co-evolve for medicine and materials.
What they build
- Autonomous Science Platform
- AI-designed biologics validated in wet-lab
- Electro-optic materials and photonic devices
Known for
- Large-scale automated data generation
- High-throughput protein purification and analytics
- Protein design and BioML modeling
- Robotic orchestration and lab simulation