Role: Senior Manager, Quality Engineering

Function: Quality Engineering / Software Testing

Location: Gurugram or Kolkata

Type: Full-time

Industry: AI, Medical SaaS, Dental Technology

About Company The company builds AI-powered SaaS for the U.S. dental market.

Its platform unifies analytics, communications, scheduling, payments, and marketing automation. Thousands of solo practices, group practices, and DSOs rely on it daily.

It is a profitable SaaS business approaching eight figures in revenue. The company is mission-driven and execution-oriented — quality is designed in, not inspected in at the end.

If you want to build in a large, under-digitized healthcare vertical and see clear, measurable impact, this is the place.

Position Overview

This role leads a team of 6–10 Quality Engineers and owns the modernization of how quality is built into the company's products. The mandate is to increase release confidence faster than QA headcount grows — through automation engineering, AI-assisted workflows, production observability, and shared quality ownership across Engineering, Product, and DevOps. This is a hands-on technical leadership position: the person in this role personally writes and reviews automation code, designs testing architecture, and investigates difficult production issues.

Role & Responsibilities

- Establish a modern quality-engineering operating model based on shared ownership across Engineering, Product, DevOps, and Quality Engineering; define risk-based testing strategies for critical customer workflows, integrations, and platforms.
- Own the architecture and evolution of web, API, integration, and end-to-end automation — personally build and maintain production-quality code in Playwright and TypeScript, including reusable libraries, fixtures, test-data systems, and parallel execution infrastructure.
- Integrate high-signal suites into CI/CD pipelines (Jenkins, GitLab CI, or equivalent); treat flaky and noisy tests as engineering defects and continuously improve execution speed, stability,



and diagnosability.
- Define testing and evaluation strategies for AI assistants, call intelligence, and automated conversation workflows — build repeatable evaluations covering accuracy, hallucination risk, context retention, fallback logic, unsafe output, privacy, and latency.
- Use AI coding assistants and agents in daily engineering workflows across test design, automation development, code review, debugging, and incident analysis; establish practical AI-assisted workflows for the team and measure their impact on development time, maintenance effort, and release-validation speed.
- Investigate production and pre-production issues using SQL, logs, traces, API requests, browser developer tools, and monitoring platforms; lead root-cause analyses that address the architectural, testing, or observability gap that allowed a defect to escape.
- Lead, coach, and develop a team of 6–10 Quality Engineers through clear goals, direct feedback, performance reviews, hiring, and career growth — raising the technical bar while scaling quality through better systems rather than linear headcount.

Must Have Criteria

- 8+ years in software quality, test automation, or quality engineering, including 3+ years of people leadership managing and developing engineers.
- 4+ years of hands-on automation experience; personally written, reviewed, debugged, and maintained production automation code within the last 12 months.
- Strong software engineering ability in TypeScript or JavaScript; experience designing automation systems from the ground up, not only scripting within an existing framework.




- Strong experience with Playwright for browser automation and API testing; candidates from Selenium or Cypress must demonstrate current coding ability and a track record of modernizing legacy automation architecture.
- Experience integrating automated test suites into CI/CD pipelines (Jenkins, GitLab CI, or equivalent) and improving execution reliability, speed, and diagnosability.
- Practical, current use of AI coding assistants or agents — able to describe specific workflows, measurable perks, limitations encountered, and a concrete case where AI output was confidently wrong and how it was caught.
- Strong production-debugging skills using SQL, logs, traces, observability systems, and network-level tooling; demonstrated track record of improving quality without proportional growth in manual QA headcount.

Nice to Have

- Experience testing AI assistants, LLM-powered products, conversational systems, call intelligence, or automated communication workflows.
- Background in healthcare SaaS, dental technology, VoIP, payments, or other business-critical platforms.
- Experience with mobile automation, distributed architectures, third-party integrations, and asynchronous processing.
- Exposure to performance, reliability, security, privacy, accessibility, or observability testing.
- Track record of transforming a traditional QA team into a modern Quality Engineering organization.

What We Offer

- Ownership of a high-impact, technically ambitious quality engineering mandate at a profitable, product-led SaaS company.
- Direct influence on architecture, tooling, and AI-assisted engineering practices across a cross-functional team.
- Autonomy and flexible scheduling within a mission-driven, execution-oriented culture.
- Opportunity to build in a large, under-digitized healthcare vertical with clear, measurable customer impact.
- Support for technical growth, career development, and contribution as a genuine engineering partner — not a process gatekeeper.

📌 Senior Manager Quality Engineering (Kolkata)
🏢 Recrew AI
📍 Kolkata