QA Automation Lead with Python – AI

Title: QA Automation Lead with Python development – AI

Location: SFO, CA

Hybrid Model

We are seeking a seasoned
QA Automation Lead
with strong
Python
development skills and practical
AI/ML
knowledge to drive quality across our product portfolio. You will own test strategy, lead a team of QA engineers, build scalable automation frameworks, and introduce
AI-assisted testing
to improve coverage, speed, and defect detection. This role combines technical leadership, hands-on automation, and cross-functional collaboration with product, engineering, and data science.

Key Responsibilities

Strategy & Leadership

• Define and own the end-to-end
  quality strategy
  , test approach, and release readiness criteria across squads.
• Lead, mentor, and grow a team of QA engineers; establish career paths, skill matrices, and a culture of continuous improvement.
• Drive
  shift-left testing
  practices, ensuring quality gates in PRs, CI/CD, and design reviews.

Automation & Frameworks

• Architect and maintain
  Python-based
  automation frameworks (e.g.,
  PyTest
  ,
  Selenium
  ,
  Playwright
  ,
  Robot Framework
  ) for UI, API, integration, and end-to-end tests.
• Implement
  data-driven
  and
  behavior-driven
  testing (BDD) with tools like
  Behave/Cucumber
  where applicable.
• Standardize test design patterns (Page Object, Screenplay, fixtures, test data services) and enforce code quality (linting, type hints, reviews).

AI-Enabled Quality

• Integrate
  AI-assisted testing
  (e.g., intelligent test case generation, flaky test detection, failure clustering, anomaly detection in logs).
• Collaborate with
  Data Science/ML
  teams to
  validate ML models
  , including dataset integrity, bias checks, model drift monitoring, and functional/non-functional validation of inference services.
• Evaluate and, where appropriate, adopt
  AI-powered test platforms
  (e.g., Mabl, Testim) or build in-house utilities using
  scikit-learn/PyTorch/TensorFlow
  for prioritization and defect prediction.

CI/CD & DevOps Quality

• Embed tests into
  CI/CD pipelines
  (GitHub Actions/Jenkins/Azure DevOps/GitLab CI), enabling parallelization, shards, and caching.
• Define and monitor
  quality gates
  (code coverage, mutation testing, static analysis, performance thresholds).
• Orchestrate environment management using
  Docker/Kubernetes
  , service mocks, test data services, and synthetic data generation.

Quality Operations

• Establish metrics and reporting (DRE, escape rate, MTTR, flaky rate, coverage, defect aging) with dashboards (Grafana/PowerBI).
• Lead
  root cause analyses
  and drive corrective/preventive actions (CAPA).
• Partner with Product and Engineering on release planning, risk assessment, and sign-off.

Required Skills & Experience

• Python:
  Advanced proficiency; building robust test frameworks, utilities, parsers, and CLI tools; strong OOP and familiarity with concurrency (asyncio), typing, packaging.
• Automation:
  Hands-on with
  PyTest, Selenium/Playwright, Requests, Robot Framework
  ; API testing (REST/GraphQL), contract testing (Pact), and service virtualization/mocking.
• AI/ML Knowledge:
  Understanding of ML lifecycle (data prep, model training/evaluation, drift monitoring), and
  AI-assisted testing
  concepts (prioritization, flaky test detection, anomaly detection). Ability to use
  pandas, NumPy, scikit-learn
  for analytics.
• CI/CD & DevOps:
  Experience integrating tests into pipelines, containerized testing, environment orchestration, and test parallelization.
• Performance & Reliability:
  Exposure to
  load/stress testing
  (JMeter/Locust/k6) and reliability checks (resilience, chaos testing basics).
• Cloud & Tools:
  Familiarity with
  AWS/GCP/Azure
  , Docker/K8s; version control (
  Git
  ), issue tracking (
  Jira/Azure Boards
  ).
• Leadership:
  Proven experience leading QA teams, setting standards, coaching, and delivering across multiple releases.