About DawerOne

DawerOne is a senior-led engineering partner to North American companies. We lead product and engineering transformations and deliver them ourselves, from architecture to production.

We work across software engineering, quality engineering, cloud infrastructure, and AI to help clients build, test, and operate reliable production systems. As our client engagements increasingly involve complex integrations, automation, and AI-enabled applications, we’re building a Quality Engineering practice that can take ownership of the entire discipline, from strategy and architecture to implementation, delivery, and continuous improvement.

The Role

We’re looking for a Principal, Quality Engineering who can architect, build, and operationalize modern quality engineering systems across client engagements.

This is a hands-on technical leadership role combining architecture, implementation, client leadership, and practice development. You’ll work directly with CTOs, CIOs, VPs of Engineering, and project sponsors from week one to assess existing systems, define the target architecture, prioritize improvements, and demonstrate measurable results.

You’ll lead technical implementation, guide engineering teams, establish quality standards, and build DawerOne’s reusable Quality Engineering capabilities across engagements. We need someone who can move from architecture diagrams to working code, from pipeline design to production implementation, and from an AI testing prototype to a controlled, measurable engineering workflow.

What You’ll Own

Quality Engineering Architecture and Automation

- Design layered test architectures spanning unit, API, contract, integration, UI, end-to-end, performance, and AI evaluation testing, with transparent ownership and quality gates.
- Build production-grade automation frameworks using Playwright and TypeScript, including reusable components, fixtures, authentication, reliable test data, and execution diagnostics.
- Develop API, integration, database, and contract tests covering authorization, business workflows, data consistency, and critical system boundaries.
- Establish measurable baselines for coverage, test reliability, execution time, escaped defects, and release confidence.
- Treat test code as production code, with maintainable architecture, type checking, code reviews, deterministic execution, and effective failure handling.

CI/CD, Infrastructure, and Test Data

- Design, implement, debug, and maintain automated testing pipelines using GitHub Actions, GitLab CI, Jenkins, Azure DevOps, or equivalent platforms.
- Integrate risk-based quality gates, smoke tests, regression suites, static analysis, and contract tests into development and release workflows.
- Provision reliable test infrastructure using Docker, cloud-native services, and infrastructure-as-code tools such as Terraform or OpenTofu.
- Establish environment isolation, secrets management, health checks, and reliable test data creation, cleanup, and management.
- Optimize test execution through parallelization, selective execution, caching, and effective infrastructure design.

AI Testing Agents and LLM Evaluation

- Build AI agents for test planning, test generation, exploratory testing, coverage analysis, failure classification, and defect reporting.




- Design bounded agent workflows with structured tool interfaces, execution limits, auditability, and appropriate access controls.
- Build repeatable evaluation frameworks for LLM-powered applications and agents using representative datasets, golden examples, edge cases, and regression suites.
- Evaluate correctness, instruction adherence, structured outputs, tool selection, retrieval grounding, and behavior when information is unavailable.
- Test for prompt injection, data leakage, and unsafe tool invocation; track model versions, latency, costs, and failure rates.
- Integrate AI evaluations into CI/CD and release qualification, using deterministic assertions where possible and validated evaluation methods where necessary.

Technical Leadership and Client Delivery

- Partner with CTOs, CIOs, VPs of Engineering, and other senior stakeholders to define quality roadmaps, technical priorities, and measurable outcomes.
- Lead technical discovery, architecture reviews, implementation planning, and delivery across complex enterprise environments.
- Build, lead, and mentor engineering teams; establish engineering standards, review architecture and code, and develop team capabilities.
- Own delivery plans, milestones, dependencies, risks, and execution, ensuring that recommendations translate into working systems.
- Help development teams incorporate testability and quality into system design and everyday engineering workflows.
- Communicate progress, risks, trade-offs, and outcomes clearly, including when quality criteria indicate that a release should not proceed.

Build DawerOne’s Quality Engineering Practice

- Establish reusable frameworks, automation libraries, pipeline templates, AI testing agents, evaluation harnesses, and implementation playbooks.
- Develop repeatable delivery methodologies and standards that improve the effectiveness of subsequent engagements.
- Contribute to technical presales, solution design, estimation, and the development of Quality Engineering offerings.
- Ensure reusable DawerOne intellectual property remains distinct from client-owned code and data.
- Turn lessons from client delivery into reusable engineering assets that strengthen DawerOne’s long-term capabilities.

What Success Looks Like

- First 30 days: Assess the existing architecture, repositories, pipelines, environments, dependencies, and failure patterns. Establish measurable baselines and agree on a prioritized implementation roadmap with client engineering leadership.
- Days 31–60: Implement high-priority automation and pipeline improvements, establish reliable test data and environment mechanisms, introduce quality gates, and begin improving observability and failure classification.
- Days 61–90: Demonstrate reliable automated execution, actionable failure reporting, and measurable improvements against agreed baselines. Document operating procedures and package reusable components for future engagements.




- Milestones will depend on the client’s starting environment and engagement scope. Longer term, success means building a capable team, improving engineering outcomes, and creating reusable capabilities that make DawerOne’s future engagements faster and more effective.

What We’re Looking For

- 15+ years of experience in software engineering, Quality Engineering, or test automation.
- Deep, hands-on expertise in Playwright and TypeScript, with a track record of architecting and implementing production-grade automation frameworks.
- Strong experience in API, integration, contract, and database testing.
- Hands-on experience building CI/CD pipelines and diagnosing automation, infrastructure, and environment failures.
- Working knowledge of Docker, infrastructure as code, cloud networking, identity and access management, secrets management, and environment isolation.
- Practical experience integrating LLMs into engineering workflows or AI-powered applications, building tool-using agents, and implementing repeatable AI evaluation workflows.
- Understanding of deterministic testing versus probabilistic evaluation, prompt injection, least-privilege access, and AI system observability.
- Proven technical leadership across engineering teams, with the ability to engage senior client stakeholders, establish standards, and deliver measurable improvements.
- Strong written communication, documentation, architectural judgment, and the ability to work independently in unfamiliar environments.
- Experience with Python, SQL, GraphQL, OpenAPI, contract-testing frameworks, Terraform, OpenTofu, Kubernetes, performance testing tools such as k6, LLM evaluation frameworks, RAG evaluation, AI-driven browser automation, and security testing is valuable. Experience with enterprise platforms such as Salesforce, MuleSoft, Flowable, or Formstack is an advantage.
- We value demonstrated implementation, technical judgment, and ownership over familiarity with a long list of tools.

Working Arrangement

- Location: Remote, anywhere in India.
- Working hours: For the upcoming engagement, the expected working window is 1:30 PM–10:30 PM IST. Hours may vary across engagements depending on client needs and time-zone overlap, so reasonable flexibility is expected.
- Travel: Occasional client or team travel as required.

Why Join DawerOne?

- Build production-grade engineering systems rather than stop at recommendations.
- Work at the intersection of Quality Engineering, infrastructure automation, and AI on real delivery problems for North American clients.
- Engage directly with senior technology leaders and influence technical architecture and implementation.
- Lead engineers and shape a growing Quality Engineering practice.
- Develop reusable engineering capabilities that compound across engagements.
- Help shape the engineering practices of a senior-led firm where senior people still write code.

How to Apply Apply through LinkedIn with your updated résumé. Shortlisted candidates will be asked to complete a technical assessment covering Quality Engineering architecture, automation frameworks, CI/CD integration, and AI/LLM testing and evaluation. We’re particularly interested in candidates who can demonstrate the systems they’ve built, the technical problems they’ve solved, and the measurable impact of their work

📌 Principal, Quality Engineering (India)
🏢 DawerOne
📍 India