Product QA

Bidgely

About The Position

We are looking for a Senior Product Quality Analyst to champion product quality across the software development lifecycle. This role will embed quality early in product development by partnering closely with Product Management, Engineering, and SDET teams to ensure features are testable, customer-ready, and meet high quality standards before release. The ideal candidate will drive a shift-left quality approach, influencing product design, validating acceptance criteria, owning product-level testing strategies, and ensuring release readiness across complex customer workflows and platform capabilities.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
Minimum three years of strong hands-on experience in Product QA, Product Assurance, or Product Quality Engineering for SaaS or complex platform products.
Proven ability to translate PRDs and user stories into comprehensive test plans, acceptance criteria, and edge-case scenarios.
Experience validating complex end-to-end user journeys across web applications, email workflows, APIs, integrations, and data-driven systems.
Strong understanding of regression planning, release validation, and defect lifecycle management.
Excellent collaboration skills with Product Managers, Engineering teams, and SDET organizations.
Experience working in fast-paced, ambiguous product environments with evolving priorities.
Proficiency with Jira, Confluence, and structured defect/test management processes.
Strong analytical skills to troubleshoot environment, configuration, and data-related issues in lower environments.

Nice To Haves

Experience working with test automation frameworks and collaborating closely with SDET teams.
Exposure to AI-assisted testing, prompt-based QA, or intelligent test generation tools.
Familiarity with lower-environment data management, pipeline dependencies, and deployment workflows.
Experience in EnergyTech, utility customer experience platforms, or other workflow-intensive B2B SaaS products.
Experience supporting release readiness across multiple pilots, customer configurations, or enterprise deployments.

Responsibilities

Own product quality throughout the feature lifecycle—from discovery and grooming through release and post-launch feedback.
Review Product Requirement Documents (PRDs), user stories, and functional specifications to ensure completeness, clarity, and testability.
Collaborate with Product Managers during backlog grooming and sprint planning to define robust acceptance criteria and identify quality risks early.
Develop comprehensive product test plans covering functional, integration, usability, regression, and edge-case scenarios.
Perform feature-level product acceptance testing before promotion to higher environments or production.
Validate complex end-to-end customer journeys spanning web applications, email workflows, integrations, APIs, and data-driven processes.
Ensure product behavior aligns with business requirements and customer expectations.
Partner closely with Engineering and SDET teams to drive quality from design through implementation.
Provide structured feedback on feature design, usability, and potential failure scenarios.
Coordinate regression planning and validate release quality for complex platform workflows.
Participate actively in defect triage, root-cause discussions, and prioritization.
Lead product QA activities supporting release readiness across multiple features and customer configurations.
Assess deployment risks and validate production readiness.
Ensure appropriate regression coverage before releases.
Support pilot deployments and customer-specific validation where required.
Continuously improve QA processes, documentation, and quality metrics.
Maintain test artifacts, defect tracking, and quality documentation using Jira, Confluence, and related tools.
Identify opportunities to improve testing efficiency through collaboration with automation teams.
Contribute to evolving quality practices, including AI-assisted testing where appropriate.