Principal, Quality Engineering

About the job

DawerOne leads engineering transformations for its clients, with senior engineering ownership from architecture to production. We are hiring a Principal, Quality Engineering to lead the quality function on client engagements, spanning both quality assurance and quality engineering. Our clients are North American enterprises running large, integrated estates: core platforms, integration middleware, workflow orchestration, and APIs on AWS. You will assess the client's current state, define the target state, and lead the team that delivers it, remaining engaged until the client can operate independently.

The role addresses strategy, process, people, and tools together. Test automation is one component of the solution, alongside skilled manual testing and AI, which is central to how DawerOne delivers and which we consider the new standard for the discipline. You will work across the client organization with stakeholders and sponsors, design quality for the entire system rather than a single layer, and support every decision with evidence. This is a hands-on leadership role: on early engagements, you will establish the foundation yourself.

This is a full-time, hybrid role based in Gurugram, with 3–4 days per month in the office and travel to client sites, including the United States, as engagements require. The role reports to the founder. Compensation is competitive for senior leadership roles and is discussed in the first conversation. Relocation expenses are the responsibility of the candidate. Hiring consists of four conversations, approximately five hours in total: a track record review, an architecture and working session, a client readout, and a conversation with the founder. Candidates should be prepared to discuss measurable outcomes and the reasoning behind their decisions.

Responsibilities

Strategy

• Assess the client's current state across strategy, process, people, and tools using the DawerOne assessment model, and present findings and a roadmap to client leadership.
• Own the test strategy, including what is tested, at which layer, by whom, and at what priority based on risk, and the appropriate balance of manual testing, automation, and AI-assisted testing.
• Build the quality roadmap and maintain alignment with the broader engagement and the client's delivery roadmap.
• Own the client and sponsor relationship, including scope, outcomes, and escalation, and communicate progress, risk, and cost in business terms to support timely decisions.
• Lead the recovery of quality programs that have lost organizational confidence: diagnose root causes, reset the approach, and restore trust.

Process

• Integrate quality into scaled Agile delivery, including multiple teams, release trains, PI planning, and cross-team dependencies.
• Improve requirement quality by partnering with product owners and developers during refinement to establish clear, testable acceptance criteria.
• Lead manual testing as a first-class discipline, including exploratory testing, end-to-end testing across connected systems, negative and boundary scenarios, data validation, and UAT support, in every sprint and ahead of every release.
• Own defect management and triage with developers and product owners, including severity assessment, root-cause classification (product, test, or environment), and closure.
• Establish release readiness as a client-owned process, with clear defect ownership, enforced quality gates, and evidence-based release decisions, and report readiness transparently, including when a release should not proceed.

People

• Navigate the client organization: identify owners, decision-makers, and sources of resistance, and drive change through the client's teams.
• Align engineering, product, and delivery leadership on quality ownership, acceptance criteria, and release governance, and facilitate the working sessions required to reach alignment.
• Develop the client's QA capability: ensure the QA team has a thorough understanding of the system under test, and prepare the client's QA lead to operate the function independently.
• Lead and grow engagement teams of 5 to 15 QA and automation engineers, supported by a delivery lead as scale requires, including interviewing every hire and defining the standards the team works to.

Tools and architecture

• Design the target-state test architecture for the entire system, covering data, APIs, user interfaces, system boundaries, and inter-system communication, as well as test-layer ownership, environments and test data, pipeline quality gates, reporting, and non-functional requirements, in partnership with the client's architects.
• Evaluate and select tools and platforms based on evidence and total cost of ownership, lead build-versus-buy decisions, and retire tools that do not deliver value.
• Set automation framework standards for engineering teams, document key decisions so they endure beyond the engagement, and establish the initial foundation yourself where a team is not yet in place.
• Establish a Centre of Excellence where the client requires one, and contribute learnings back to the DawerOne platform and playbooks.

AI

• Embed AI in how the team works, as DawerOne's practice and the new standard: design the supporting architecture, including agents, MCP servers, skills, and repository conventions files, and build the initial components yourself where a team is not yet in place.
• Direct AI engineers working alongside QA and automation engineers, and prioritize what they build.
• Govern the use of AI in the client's test suite, including what it may generate, what requires human review, and the quality standard every test must meet.

What success looks like

Within the first six months

• Strategy: The quality strategy and roadmap are agreed with client leadership and sponsors, aligned with the wider program, and understood by every team they affect.
• Process: Quality is integrated into how product and engineering work: testable acceptance criteria at refinement, a working definition of done, defect triage, and a release-readiness process in operation.
• Architecture and framework: The target-state test architecture is approved by the client's architects, and the automation framework is in place to agreed standards across the data, API, integration, and UI layers.
• Pipeline: Tests run in CI/CD with enforced quality gates on the critical path, and every failure is triaged to an owner.
• Visibility: Dashboards give client leadership a current, evidence-based view of coverage of high-risk workflows, suite reliability, and release readiness.
• AI: AI tooling is in daily use by the team, under the governance you have defined.

Within twelve months

• Measurable improvement: Results against the baseline from your assessment are demonstrable: escaped defects, flaky rate, regression cycle time, and release frequency.
• Evidence-based releases: Release decisions are made on evidence, and the client's pipeline blocks a defective change without DawerOne involvement.
• Client independence: The client's QA lead and teams operate the function independently, including a Centre of Excellence where one is required.
• Team: You have hired and developed the engagement team, and are leading a second engagement.
• Contribution: What you have learned has been contributed back to the DawerOne platform and playbooks.

Minimum qualifications

What matters most

The following are the most important qualifications for this role. Years of experience are indicative; a demonstrated track record is required. All claims are verified during the interview process and through reference checks.

• You have established a quality engineering function at least once, for a client or within a product organization, and can describe its state one year later.
• You have led at least one quality engineering transformation end to end, from assessment to a sustained operating model, with measurable before-and-after results.
• You have entered an unfamiliar client organization, identified owners and decision-makers, presented an assessment to a CTO or VP of Engineering, and delivered the resulting change through the client's teams.

Experience

• 15+ years in quality engineering, including 10+ years in test automation.
• Experience leading teams of 5 to 15 engineers through delivery against committed deadlines, including in scaled Agile environments such as SAFe, with multiple teams, release trains, PI planning, and cross-team dependencies.
• Experience running the QA function within a delivery program, including test strategy, risk-based planning, defect triage, UAT, and release sign-off, combined with strong hands-on testing skills: the ability to work alongside testers, test a business process end to end across systems, and identify issues that scripted tests miss.
• Experience building a quality roadmap and presenting it to project sponsors, and selecting tools and leading build-versus-buy decisions based on evidence and total cost of ownership.
• Experience owning test architecture across multiple teams, with a thorough understanding of every system layer and how they fit together: data, APIs, user interfaces, system boundaries, and inter-system communication, including contracts, integrations, middleware, events, and queues.
• Experience designing automation frameworks from the ground up at least twice, with at least one still in production use. Deep expertise in a modern automation stack such as Playwright with TypeScript, and the ability to design for the client's technology stack.
• Working knowledge across the quality pipeline, tools, and technologies, including CI/CD platforms such as GitHub Actions, Jenkins, or Azure DevOps; API and contract testing with Postman or Pact; performance testing with k6 or JMeter; Jira with a test management tool such as Xray, TestRail, or Zephyr; SQL for data validation; and AI coding tools such as Claude Code, Cursor, or Copilot.
• Experience remediating an automation program that had lost stakeholder confidence, with measurable improvement in flaky rate and pass rate, and introducing a CI quality gate that blocked a production release.
• Hands-on experience building with AI, including agents, MCP servers, skills, and conventions files such as CLAUDE.md, in production work, and directing AI engineers within a delivery team while ensuring all output is reviewed and owned.

Ways of working

• Excellent written and spoken English, for working directly with North American clients and their leadership.
• Ability to read code and AI-generated tests at a level sufficient to uphold standards, and to decline a client request while clearly explaining the trade-offs.
• Ability to work 1:30pm to 10:30pm IST, to be in the Gurugram office 3–4 days a month, and to travel to client sites, including the United States, as engagements require.

Preferred qualifications

• Experience working directly with US or North American stakeholders and sponsors is highly preferred.
• A valid US B1/B2 visa.
• Experience with enterprise platforms and integration technologies such as Salesforce, MuleSoft, or Flowable.
• A professional services or consulting background, including large programs with executive sponsors.
• Experience establishing a quality engineering Centre of Excellence.
• Experience within a product organization with a mature release process.
• Familiarity with BrowserStack, AWS, and cloud CI platforms.