Job Description

- Work alongside AI agents as co-workers within our AI-SDLC framework — using Anthropic Claude Code, GitHub Copilot, and AWS Bedrock throughout design, development, testing, deployment, and maintenance cycles
- Drive work from Jira tickets and Confluence documentation as the source of truth for requirements, decisions, and context
- Leverage deep domain and product knowledge to evaluate and challenge requirements — ensuring they are precise, complete, and structured for effective processing by both human engineers and AI agents
- Participate actively in Agile ceremonies — sprint planning, stand-ups, retrospectives, and backlog refinement — to keep delivery on track and priorities aligned
- Surface and mitigate quality risks before they escalate — proactively communicating test coverage gaps, flagging scope concerns during planning, and helping keep the team's quality commitments on track
- Own the test strategy and automation architecture — spanning functional, end-to-end (Playwright), BDD, performance (JMeter), and data validation layers
- Build and maintain robust Python-based test frameworks and BDD feature suites that align test coverage to biopharma business requirements
- Design and govern JMeter performance test plans; analyse results and drive remediation with development teams
- Design data validation pipelines for PostgreSQL and Snowflake
- Serve as the go-to QA engineer for the harder test challenges — the person the team relies on when complexity, regulatory risk, or system ambiguity is highest
- Produce clear test strategy documents, defect trend analyses,



and quality reports that inform team and stakeholder decisions; communicate quality status and risk effectively to both technical and non-technical audiences
- Incorporate pharma manufacturer client needs and regulatory requirements into test coverage decisions; participate actively in incident responses and quality reviews that have direct client impact
- Apply robust analytical and problem-solving skills to diagnose complex test failures — anticipating system failure modes and designing test coverage for them proactively rather than reactively; evaluate quality trade-offs and drive decisions with appropriate rigour
- Demonstrate full accountability for your own work and the team's quality output — holding yourself answerable to team-level quality outcomes, not just individual test deliverables; proactively managing risks, communicating progress, and owning quality end-to-end
- Lift the overall quality output of the team — through proactive test design collaboration, knowledge sharing, unblocking, and consistently raising the bar on what the team ships
- Stay current with the team's evolving test toolset — including AI-augmented testing practices, Playwright updates, BDD patterns, and biopharma regulatory developments — and actively bring relevant updates into team practices
- Partner effectively across backend developers, UI/UX developers, product analysts, and domain stakeholders — communicating clearly within a geographically distributed team
- Mentor junior QA engineers and champion quality best practices across the team
- Evaluate and integrate AI-powered testing tools into the QA workflow

📌 Sr. Software Quality Automation Engineer (Pune)
🏢 IntegriChain
📍 Pune