Quality Platform Lead

In India, Branch operates as a regulated digital lending institution and Middle Layer NBFC, building trusted and accessible financial products for millions of customers across the country. Our 250+ member India team is growing rapidly and works across technology, data science, risk, product, and operations to solve high-impact problems at scale. 

Certified as a Great Place to Work in 2025, Branch offers the opportunity to build meaningful careers while shaping the future of inclusive fintech in one of the world’s fastest-growing digital economies.

About Role:
At Branch, quality has always been the responsibility of the engineers, product managers, and business owners who build and ship the product. We deliberately do not have a traditional QA team gating releases — we believe the accountability for what goes to production must sit with the people building it, not with a separate function checking their work.

As the Quality Platform Lead, you will build and lead a small, high-leverage team that audits production against our stated expectations — functional, behavioral, regulatory, and experiential — and reports honestly on what they find. You will not own release gates. You will not sign off on builds. Engineers and Product retain full ownership of what they ship and when. Your team's mandate is to be the independent, automation-first lens on whether what's running in production actually matches what we said we were building, and to make any drift visible to the people who can fix it.

You will architect and champion a continuous, automated quality-auditing ecosystem. Instead of acting as a release gatekeeper, this leader will build smart automation and AI-driven agents to continuously evaluate production against company standards, providing the high-fidelity feedback loops our engineering, product, and business teams need to maintain ultimate accountability.

This is a builder role. You will define the operating model from scratch, hire a small team of strong engineers, and lean heavily on automation, agents, and continuous production verification rather than manual test cycles. Success looks like a team that catches more, manually does less, and grows the organization's confidence in its own output without becoming a bottleneck to it.

Responsibilities

• Establish charter, operating principles, success metrics, and the team itself. Reinforce in every process that this is an audit function, not a release gate.
• Design and operate an automation-first stack: AI agents, synthetic monitoring, production probes, behavioral diffing, and continuous sampling. 
• Design and execute a continuous non-intrusive production auditing strategy to catch subpar experiences, regressions, and drift. Establish measurable metrics across user experience and system behavior. Continuous automated coverage that scales with the product instead of a pile of manual test cases.
• Translate audit findings into actionable insights for Engineering and Product. Partner on root-causing systemic issues without taking ownership of their bug fixes, and build dashboards that give the organization real-time visibility into production quality.
• Recruit, grow, and empower a team of strong builders first and quality specialists second. Hold a high bar on technical depth.
• Be a credible technical voice on incidents, regressions, and quality patterns. Stay hands-on enough to contribute to the team's stack.
• Own your team's full delivery cycle and engineering standards: code review, testing discipline, observability, and responsible AI use.
• Represent the team's findings through clear written reports, metrics, and well-run forums. Resist pressure to convert audit findings into release blocks.

• 8+ years building production software, with at least 2 years leading engineers directly. Some of that experience in environments where you owned quality, reliability, or production verification at scale.
• Track record of building automation-first quality or verification systems — test infrastructure, synthetic monitoring, production probing, chaos or behavioral testing rather than managing manual QA.
• Hands-on experience with LLMs, AI agents, or sophisticated testing tools to automate non-deterministic flows, and a sharp view on where modern AI changes the economics of test and audit work.
• Deep familiarity with modern automation frameworks (Playwright, Cypress), CI/CD, and observability tools (Datadog, New Relic). You think in terms of sampling, blast radius, and error budgets rather than green/red test suites.
• Strong foundation in backend or full-stack systems, distributed systems, and data modeling. Mobile or AI systems experience a plus.
• Strong conviction in an engineering-owned quality model and a resistance to letting a quality function become a scapegoat for bugs.
• Experience hiring engineers and calibrating a team's bar, including hard calls on performance.
• Exceptional, highly structured communication skills, with the ability to influence teams using data and operate effectively across asynchronous environments.
• Background working in fast-paced, high-scale environments; experience in fintech, payments, lending, AI, or mobile is a strong plus.