Senior Director, Software Development, Test Automation

Lila SciencesSan Francisco, CA
$260,000 - $390,000

About The Position

We're hiring a Senior Director, Software Development, Test Automation Systems to architect and build Lila's test automation platform and quality engineering practice for our AI-powered scientific and lab automation products. Reporting to the VP of Engineering, you'll own the test automation system, CI/CD test infrastructure, AI-driven test tooling, and the eval discipline that hold the bar across our SDLC. This is a builder-leader role. You will drive the quality vision, write requirements, make sharp build-vs-buy calls, drive execution, and build and lead a small (3–5 person) team that delivers leverage. The operating model is federated: you own the platform, standards, and metrics; engineering teams own test execution. You scale through tooling and influence. As you scale into this role, you'll also stand up the QC framework for our lab automation system — the validation patterns, harnesses, and contracts that science operations teams will operate day-to-day. Data integrity and ALCOA+ compliance are foundational to everything you build.

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/engineer. You write designs your team wants to read and review.
  • Python and/or Typescript hands on expertise is highly desirable.
  • Deep CI/CD expertise. GitHub Actions or equivalent at scale, monorepo build/test orchestration (Nx, Turborepo, or Bazel), test parallelization and caching, hermetic environments, ephemeral preview envs, flake quarantine, and test impact analysis
  • Demonstrated build-vs-buy judgment. You've made and defended decisions on test infra, eval platforms, browser/device clouds, and observability — and can articulate the TCO and signal trade-offs that drove them
  • Hands-on AI-driven test automation experience. Using LLMs to generate, maintain, or triage tests in production, with rigorous eval validation. Fluency with eval frameworks
  • Track record of standing up a test automation platform that engineering teams adopted — not one bolted on
  • Working knowledge of Google's SRE practices and a point of view on when they apply to pre-production quality
  • Metrics-driven leader who drives outcomes through platform leverage and influence, not gatekeeping
  • Customer- and UX-first instincts: treats test automation as a vehicle for user experience, not a cost center

Nice To Haves

  • Experience in GxP-regulated environments or scientific data integrity programs
  • Experience with lab automation, LIMS, or other instrument-driven systems
  • Multi-tenant SaaS quality at scale
  • Exposure to event-driven systems, agent orchestration frameworks, or MCP
  • Performance/load testing or chaos engineering background

Responsibilities

  • Architect and ship the test automation platform
  • Design and build the test automation platform — frameworks, fixtures, golden datasets, test orchestration, and reporting — that the engineering org adopts by default
  • Set standards across unit, integration, contract, end-to-end, regression, performance, and chaos testing for backend services, the frontend monorepo, and data pipelines
  • Treat platform adoption, flake rate, and time-to-signal as first-class engineering metrics
  • Make build-vs-buy decisions with conviction
  • Own the buy/build/borrow strategy across test infrastructure, eval platforms, browser/device clouds, observability, and lab QC tooling
  • Justify every choice with TCO, signal quality, integration cost, and time-to-leverage — and revisit decisions as the org and tech landscape evolve
  • Bias toward leverage: buy commodity capabilities, build the differentiators (Lila-specific AI evals, lab QC, scientific data integrity)
  • Modernize CI/CD for fast, reliable signal
  • Own the test execution layer of CI/CD: parallelization, caching, hermetic environments, ephemeral preview envs, and affected-only test selection across our Nx monorepo/microservices.
  • Build retry, quarantine, and impact-analysis systems so signal stays sharp as the org scales
  • Drive change-failure rate, MTTR, Test effectiveness, pipeline efficiency, coverage, and PR-to-prod lead time as outcomes
  • Drive AI-driven test automation
  • Apply LLMs across the full test lifecycle: test generation from specs and PRs, self-healing UI tests, synthesis, visual regression with vision models, and AI-assisted failure triage
  • Validate every AI-generated test through evals — no LLM-authored test ships without proof it doesn't degrade signal
  • Establish the eval discipline for Lila's AI/agent stack: golden datasets, rubrics, regression suites, offline + online evaluation pipelines
  • Define and operate the quality metrics system
  • Define quality SLOs and adoption metrics by team and service: coverage, escape rate, MTTR, change-failure rate, eval pass rate, lab QC violation rate
  • Build dashboards that make quality visible from PR to executive review
  • Apply Google SRE practices to prioritize where investment goes
  • Mid-long term - Stand up the QC framework for lab automation
  • Design the validation framework, harnesses, and contracts that lab and Science Ops teams will operate
  • Embed ALCOA+ principles: data integrity, audit trails, lineage from sample → instrument → output
  • Partner with Research Ops on pre-flight, in-flight, and post-flight validation patterns for autonomous lab execution
  • Lead and coach across the engineering org
  • Build a 3–5 person team of test automation engineers focused on platform leverage, not on writing tests for other teams
  • Coach engineering teams on test design, quality investments, and adoption — make it cheaper to test well than to ship blind
  • Translate UX and customer issues into testable contracts and platform improvements

Benefits

  • competitive base compensation with bonus potential and generous early-stage equity
  • medical, dental, and vision coverage
  • employer-paid life and disability insurance
  • flexible time off with generous company wide holidays
  • paid parental leave
  • an educational assistance program
  • commuter benefits, including bike share memberships for office based employees
  • a company subsidized lunch program
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service