About Contour

Contour Software has grown from a dozen people to over 2,000 staff across 3 cities, in less than 14 years.
 

As a subsidiary of Constellation Software Inc., we are proud to be part of a global enterprise software conglomerate that has grown to become one of the top 10 software companies in the world, with employees and customers in 100+ countries. With a broad-based and ever-growing portfolio of market-leading, vertical-market enterprise solutions covering more than 100 industry domains in predominantly mature markets, CSI's recipe creates the perfect environment for professionals to build fulfilling, long-term careers.
 

What started as an R&D & Accounting back-office, has progressed into a full-service Global Centre serving all functions and departments, at the divisional as well as operating group/corporate level. Today Contour employees, located in Karachi, Lahore & Islamabad, are serving CSI divisions located in time zones spanning the globe, from Sydney to Vancouver. With the global growth of Constellation as the wind in our sails, we are only just getting started!

The Position

We are seeking an experienced Senior SQA Automation Analyst to help expand and mature our test automation capabilities across a complex, highly configurable SaaS platform.

The primary focus of this role will be to accelerate Playwright automation adoption, improve regression coverage, strengthen CI/CD quality gates, and support the organization's AI-assisted testing initiatives.

The ideal candidate will possess strong hands-on experience with Playwright, API automation, automation framework design, test data management, and AI-assisted quality engineering practices. The individual will work closely with Product Managers, Developers, Architects, DevOps, and QA teams to improve quality processes and reduce defect leakage.

The selected individual will work from Contour Software's Lahore office as an extension of the division's R&D team.

Key Responsibilities

Quality Frameworks and Architecture

• Define and evolve quality engineering frameworks across functional, API, integration, contract, end-to-end, performance, resilience, accessibility, security, and data quality testing.

• Select appropriate testing methods and layers based on business risk, system behaviour, feedback speed, and maintenance cost.

• Build reusable automation components, test data utilities, reporting capabilities, and reference implementations.

• Establish reliable approaches to test environments, synthetic data, setup, cleanup, and repeatable execution.

• Evaluate frameworks and tools through practical pilots, considering effectiveness, maintainability, integration, scalability, and total cost.

Quality Throughout the AI-DLC

• Embed quality practices into requirements, design, construction, release, and operations.

• Partner with Product and Engineering to translate business intent into clear acceptance criteria, business rules, and verifiable outcomes.

• Identify ambiguity, missing scenarios, integration risks, and nonfunctional requirements before implementation.

• Establish verification practices for both human- and AI-generated code, tests, and technical artifacts.

• Maintain traceability between requirements, identified risks, verification evidence, and release decisions.

• Promote independent verification so generated tests challenge implementation assumptions and detect incorrect behavior.

AI-Assisted Quality Engineering

• Apply AI to test design, automation development, exploratory testing support, failure investigation, refactoring, and documentation.

• Review AI-generated assets for correctness, meaningful assertions, security, duplication, and maintainability.

• Develop reusable domain context, examples, and guidance that improve the quality of AI-assisted engineering.

• Evaluate agentic testing workflows with appropriate permissions, review points, and reproducible evidence.

• Measure improvements in feedback speed, defect detection, and engineering effort.

• Where products include AI capabilities, establish evaluations for accuracy, grounding, permissions, unsafe actions, consistency, latency, and cost.

Continuous Validation and Release Confidence

• Integrate automated validation into developer workflows and CI/CD pipelines.

• Define proportionate quality gates based on change risk and business criticality.

• Improve test reliability, execution time, failure diagnostics, and the credibility of automated results.

• Distinguish product defects from test, data, environment, and infrastructure failures.

• Provide clear visibility into coverage gaps, unresolved risks, and release readiness.

• Partner with DevOps and Security to incorporate relevant checks, recovery validation, and evidence collection.

Product Quality and Production Learning

• Prioritize verification of business-critical workflows, including transactions, permissions, integrations, and data integrity.

• Retain exploratory testing for unfamiliar behavior, usability, complex interactions, and failure recovery.

• Use production incidents, support trends, operational telemetry, and customer feedback to refine quality priorities.

• Convert recurring failures into reproducible scenarios and preventive checks.

• Partner with appropriate specialists to translate applicable security, privacy, and compliance requirements into verifiable controls.

Quality Center of Excellence Enablement

• Establish practical standards, reference architectures, reusable assets, and adoption guidance.

• Serve as a technical advisor for complex testing and quality engineering challenges.

• Assess team practices and recommend improvements appropriate to product needs and maturity.

• Coach developers and QA engineers in test design, automation, AI-assisted verification, and failure analysis.

• Facilitate knowledge sharing and encourage consistent practices while allowing justified product-specific choices.

• Help teams own quality within their everyday engineering work.

Required Skills

• Bachelor’s degree in computer science, Software Engineering, Information Technology, or related discipline.

• 8+ years of professional QA experience with strong hands-on AI & Automation expertise.

• Significant progressive experience in software quality engineering, including hands-on automation architecture and technical advisory responsibilities.

• Deep knowledge of quality frameworks, testing methodologies, test design techniques, and risk-based testing.

• Strong programming and debugging skills, with experience building maintainable automation and reusable components.

• Practical expertise in API and integration testing, data validation, test data management, and complex workflow verification.

• Experience integrating automated validation into CI/CD pipelines and improving feedback reliability.

• Ability to work across different technology stacks, product architectures, and levels of engineering maturity.

• Practical experience with AI-assisted engineering tools and critically evaluating their outputs.

• Experience defining meaningful quality measures and using evidence to prioritize improvements.

• Strong communication, collaboration, and coaching skills across geographically distributed teams.

Preferred Experience

• Establishing or advancing a Quality Center of Excellence.

• Testing configurable SaaS platforms, commerce, payments, subscriptions, POS, or logistics workflows.

• Performance, resilience, accessibility, security, or observability practices.

• Evaluating AI-enabled products, retrieval-augmented generation, or agentic workflows.

• Modernizing quality practices across a mix of established and evolving systems.

Measures f Success

• Success will be assessed against agreed baselines and product priorities, including:

• Improved verification of critical business rules and workflows. 

• Reduced customer-impacting defects and repeat incidents.

• Faster, more trustworthy engineering feedback and failure diagnosis.

• Improved automation reliability and maintainability.

• Adoption of useful CoE standards and reusable capabilities.

• Demonstrable benefits from AI-assisted quality practices.

• Stronger release evidence and clearer visibility into residual risk.

Soft Skills & Collaboration

• Ability to collaborate effectively with geographically distributed Product, Development, QA, Architecture, and DevOps teams.

• Strong analytical, debugging, problem-solving, verbal, and written communication skills.

• Self-driven and able to work independently in a fast-paced delivery environment.

Exciting Benefits we offer:

• Market-leading Salary
• Medical Coverage – Self & Dependents
• Parents Medical Coverage
• Provident Fund
• Employee Performance-based bonuses
• Home Internet Subsidy
• Conveyance Allowance
• Profit Sharing Plan [Tenured Employees Only]
• Life Benefit
• Child Care Facility
• Company Provided Lunch/Dinner
• Professional Development Budget
• Recreational area for in-house games
• Sporadic On-shore training opportunities
• Friendly work environment
• Leave Encashment

Disclaimer: At Contour, we attribute our success to the unique contributions of our diverse staff. We’re committed to fostering a culture of respect that thrives on the varied perspectives and experiences of all individuals we recruit, employ, promote, and compensate. Since day one, we’ve adhered to a policy that champions a work environment honoring the worth and dignity of each person while being free from all forms of employment discrimination.

In our continuous effort to promote inclusivity, we extend our commitment to individuals with special needs by providing reasonable accommodations. We actively encourage qualified individuals with special needs to apply for the various openings within our company. Should you require assistance in completing the application process or have any inquiries regarding special facilities, please do not hesitate to contact our HR team. Your unique talents and abilities are welcomed and valued here.