layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Senior Director, Software Development, Test Automation at Lila Sciences | LAYIQ

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
First 6–12 Month Outcomes
First 90 days: Establish baselines — flake rate, time-to-signal, change-failure rate, coverage, and current build-vs-buy footprint — and publish a quality scorecard with the first set of SLOs. Hire or onboard the initial 1–2 platform engineers.
By 6 months: Ship v1 of the test automation platform adopted by at least one flagship engineering team by default; land CI/CD test-execution improvements (parallelization, affected-only selection, flake quarantine) with measurable time-to-signal reduction. Stand up the eval discipline (golden datasets, rubrics, regression suites) for the AI/agent stack.
By 12 months: Drive default platform adoption across the engineering org; demonstrate AI-driven test automation in production with eval-gated rollout. Deliver the first operating version of the lab automation QC framework with ALCOA+ audit trails, validated end-to-end with Science Ops. Quality is visible from PR to executive review via live dashboards.

Senior Director, Software Development, Test Automation

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