QA Lead

About the role

You will own the end to end quality strategy for Giga's AI agent platform, setting the definition of done for every release. You will design and execute test plans that cover voice, chat, and email workflows while validating non deterministic AI outputs for accuracy, tone, and hallucination risk. You will build the testing processes and quality gates from the ground up, enabling fast yet reliable feature deployments. You will manage a distributed QA team, aligning offshore testers with the San Francisco engineering and product groups to maintain consistent standards. You will act as the primary quality owner, pushing back when risk is high and allowing releases to move forward when confidence is solid. You will document clear defect reports and traceability so engineering can resolve issues efficiently. If you thrive in ambiguous, fast moving environments and care deeply about reliability, this role gives you direct influence over how quality scales with the business.

Key facts

What you'll do

• Define and evolve the test strategy for our voice, chat, and email AI agents, creating acceptance criteria, coverage matrices, and risk based plans for each new feature.
• Design and run execution protocols for AI agent validation, testing conversational flows, emotional tone, hallucination detection, and edge case behavior across deterministic and non deterministic outputs.
• Own the QA gate for release management, coordinating test cycles, managing regression suites, and signing off on production readiness before any customer facing deployment.
• Build and operate the testing processes and documentation that allow QA to scale as the product and engineering organization grow, including test automation planning and continuous improvement.
• Manage a distributed QA team across San Francisco and offshore locations, assigning work, performing code and conversation reviews, setting quality standards, and keeping the team synchronized across time zones.
• Classify, prioritize, and document defects with clear reproduction steps and expected behavior so engineering teams can efficiently investigate and fix issues in the AI agent workflows.
• Partner closely with product managers and engineers to understand roadmap initiatives, surface potential quality risks early, and influence release decisions based on test evidence.
• Drive quality culture by mentoring QA engineers, establishing best practices, and evangelizing quality minded thinking across product, design, and engineering teams.

Requirements

• Bring 7+ years of experience in QA or quality assurance, with a track record of leading test efforts for complex, customer facing software products.
• Have managed or led distributed QA teams, ideally across time zones, and know how to keep offshore testers productive, motivated, and aligned with the San Francisco engineering team.
• Demonstrate mastery of test planning, including the ability to analyze features, identify edge cases, and construct test strategies that catch issues engineers might overlook.
• Show experience testing conversational AI, voice systems, chatbots, or other non deterministic products where correct is not a single fixed answer and requires nuanced evaluation.
• Exhibit strong written and verbal communication skills, delivering clear bug reports, thorough test plans, and confident status updates to both technical and executive stakeholders.
• Prove you can balance rigor with speed, pushing back when risk is unacceptable while also recognizing when quality is sufficient for the current stage of the company.
• Have a background building QA functions from scratch, defining processes, selecting tools, and establishing quality standards without relying on existing frameworks.
• Express genuine interest in AI and a desire to explore what quality assurance means for products that did not exist five years ago.

Nice to have

• Experience working with voice AI platforms, speech to text systems, or multimodal conversational agents.
• Familiarity with tools and frameworks used for large language model evaluation and automated testing of generative outputs.
• Background in regulated industries where compliance, auditability, and detailed traceability are required.
• Experience collaborating closely with product managers and data science teams to iterate on AI agent behavior and prompt design.

Practical notes

This role is full time and based in San Francisco. The position involves regular work across time zones with offshore teams, requiring availability during overlapping hours for coordination. Giga is an equal opportunity employer committed to diversity and inclusion in all employment decisions.