> Markdown version of [/jobs/ext/2060093-lead-test-automation-engineer-with-playwright](https://www.wearedevelopers.com/jobs/ext/2060093-lead-test-automation-engineer-with-playwright). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

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# Lead Test Automation Engineer with Playwright

- **Company:** Capgemini
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $97,371.0 - $121,364.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Continuous Integration, DevOps, Distributed Systems, Python (Programming Language), OpenShift, Selenium, Software Engineering, Test Execution Engine, TypeScript, Workflow Management Systems, Delivery Pipeline, Large Language Models, Snowflake, Backend, Event Driven Architecture, Gherkin, Kubernetes, Playwright, Enterprise Integration, Data Management, Virtual Agents, Api Design, Data Pipelines, Microservices
- **Published:** August 14, 2026
- **Apply:** https://dejobs.org/x/x/7EE71466ED8047C79EF6AC8CAD2D8D0C/job/

## About the Role

* 8+ years of software engineering experience , with significant recent experience in backend and platform engineering.
 * Proven track record re-platforming an IDE-centric, desktop, or developer-facing tool into a scalable shared service.
 * Experience building highly available distributed systems and internal developer platforms.

Technical Skills

 * Strong proficiency in Python and/or TypeScript .
 * Deep expertise in:
 * API design
 * Event-driven systems
 * Workflow orchestration
 * Microservices architectures
 * Experience building services on Kubernetes , OpenShift , or ROSA environments.

Quality Engineering Expertise

 * Strong background in automated testing strategies and frameworks.
 * Hands-on experience with:
 * Gherkin / BDD
 * Playwright
 * Selenium
 * CI/CD pipeline integration
 * Experience developing and maintaining large-scale test execution platforms.

AI, Agents & Automation

 * Practical experience with agentic AI frameworks such as:
 * LangGraph
 * CrewAI
 * Strands
 * Similar orchestration frameworks
 * Ability to design deterministic control mechanisms around probabilistic AI systems.
 * Understanding of LLM economics, token usage optimization, and cost-aware AI solution design., Experience with ROSA/OpenShift platform operations .Familiarity with Snowflake , AI Gateway architectures, and enterprise AI integration patterns.Ownership experience in:
 * Test Data Management (TDM)
 * Synthetic data pipelines
 * Data provisioning platforms

Experience leading modernization initiatives within complex brownfield environments.Knowledge of insurance domain systems and testing practices.

## Description

Platform Re-Architecture & Service Evolution

 * Lead the re-platforming of the existing IDE-bound QE harness into a scalable, multi-tenant ORBIT service.
 * Design and implement headless execution capabilities with API-driven and event-driven interfaces.
 * Build durable orchestration frameworks supporting:
 * Asynchronous execution
 * Queued workloads
 * Scheduled test runs
 * Long-running workflows
 * Failure recovery and retry mechanisms
 * Establish robust service-level reliability, observability, and operational excellence standards.

End-to-End Quality Engineering Integration

 * Integrate the harness into the E2E quality engineering spine, including:
 * Requirements
 * SpecRecord
 * CodeGen
 * Test Generation
 * Test Execution
 * Promotion workflows
 * Enable seamless automation flow across development, testing, and release pipelines.

Architecture & Platform Integrations

 * Integrate with:
 * TDM (Test Data Management) two-lane architecture
 * Repo Knowledge Plane
 * Internal engineering platform services and APIs
 * Design scalable service contracts and event schemas to support ecosystem-wide interoperability.

Quality Signals & Promotion Intelligence

 * Design telemetry and observability frameworks for execution analytics.
 * Implement:
 * Flake detection
 * Stability scoring
 * Reliability trending
 * Promotion gating mechanisms
 * Drive data-informed release decisions through measurable quality signals.

AI and Agentic Framework Integration

 * Build deterministic workflows around agentic and LLM-powered capabilities.
 * Develop controls that balance autonomous behavior with engineering predictability and governance.
 * Optimize token consumption and LLM operating costs as first-class architectural constraints.

Engineering Leadership

 * Define platform engineering best practices, standards, and patterns.
 * Mentor engineers and contribute to architecture reviews and technical strategy.
 * Partner with QE, platform engineering, DevOps, and AI engineering teams to drive adoption and platform success.


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