Description
Storyful is building AI-native products on top of complex, high-volume, multi-source content. We are looking for a hands-on Senior QA Automation Engineer to raise the quality bar while increasing delivery speed through AI-augmented engineering.
This is a senior individual contributor role for someone who treats AI as a core part of their craft , using coding agents, LLMs, and evaluation frameworks to scale quality faster than headcount.
You will design and build the automation, evaluation, and quality foundations that enable engineers to own quality, while ensuring our products remain reliable, explainable, and trusted , even as they become increasingly probabilistic.
Responsibilities
Design and build AI-augmented automation systems
- Build and evolve scalable automation frameworks across web UI, APIs, and data pipelines (Playwright / TypeScript)
- Use AI coding agents (e.g. Claude Code) to generate, refactor, and maintain test suites at scale
- Translate natural-language acceptance criteria into executable, maintainable tests
- Define reusable testing patterns that enable engineers to own automation within their domains
- Continuously reduce flakiness using trace analysis, observability, and AI-assisted failure triage
Enable shift-left, engineering-led quality
- Partner with engineers to embed testing early in the development lifecycle
- Define pragmatic, risk-based test strategies across unit, integration, contract, and E2E layers
- Establish clear definitions of done, quality gates, and release readiness standards
- Build tooling and frameworks that allow teams to move fast without relying on central QA
Build QA practices for AI/LLM-powered features
- Design evaluation pipelines for LLM-driven features using:
- Golden datasets and regression harnesses
- Semantic similarity scoring
- LLM-as-a-judge evaluation patterns
- Detect and prevent issues such as prompt drift, hallucinations, retrieval failures, and schema regressions
- Test agentic workflows end-to-end (tool use, multi-step reasoning, failure modes)
- Partner with data science to define measurable quality signals (precision, recall, grounding, drift)
Integrate quality into CI/CD and delivery
- Embed automation and evaluation into CI/CD pipelines for fast, reliable feedback
- Define and tune meaningful quality gates based on real metrics (not ceremony)
- Support release processes with high-confidence signals and rollback readiness
Drive debugging, observability, and defect excellence
- Investigate complex issues across distributed systems using logs, traces, and metrics
- Improve observability, including LLM trace visibility (e.g. Langfuse)
- Establish strong defect triage, categorisation, and reporting practices
- Use data (leakage, flake rate, MTTR, escape rate) to continuously improve quality
Own non-functional and AI-specific risk testing
- Embed security testing into automation (OWASP, API security, auth flows)
- Test AI-specific risks (prompt injection, jailbreaks, unsafe tool use, data leakage)
- Collaborate on performance, resilience, and scalability testing where it matters most
Requirements
- Proven experience as a Senior QA Automation Engineer / SDET in production environments
- Strong hands-on experience with Playwright (or equivalent) using TypeScript
- Demonstrated use of AI coding tools (e.g. Claude Code) as part of daily workflow
- Strong software engineering fundamentals and ability to write maintainable production-grade code
- Experience designing automation frameworks and test strategies end-to-end
- Deep understanding of CI/CD and integrating automation into delivery pipelines
- Strong debugging and observability skills across distributed systems
- Experience driving shift-left practices and enabling engineers to own quality
- Solid understanding of databases, APIs, and test data validation (SQL, REST/GraphQL)
- Security-aware mindset (OWASP, secure test design)