Senior QA Automation Engineer with deep expertise in Python, Playwright, BDD, and SQL, working in an AI-augmented SDLC for life sciences market access platform.

About the Company

IntegriChain is the data and application backbone for market access departments of Life Sciences manufacturers. The company delivers the data, the applications, and the business process infrastructure for patient access and therapy commercialization. More than 250 manufacturers rely on the ICyte Platform to orchestrate their commercial and government payer contracting, patient services, and distribution channels. ICyte is the first and only platform that unites the financial, operational, and commercial data sets required to support therapy access in the era of specialty and precision medicine. Headquartered in Philadelphia, PA (USA), IntegriChain has offices in Pune, India, and Medellín, Colombia.

Role Overview

We are seeking a Senior Software Quality Automation Engineer to join our Pune team. This role is a hands-on technical leadership position within a fast-paced, AI-augmented software development lifecycle. You will work alongside AI agents using tools like Anthropic Claude Code, GitHub Copilot, and AWS Bedrock to design, develop, test, deploy, and maintain our platform. You will own the test strategy and automation architecture with a primary focus on data quality, spanning ETL/ELT pipeline validation, functional, end-to-end, BDD, and performance testing layers. You will serve as the go-to QA engineer for the most complex test challenges and mentor junior team members.

Key Responsibilities

• Work alongside AI agents within an AI-SDLC framework, using tools such as 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 to ensure they are precise, complete, and structured for effective processing by both human engineers and AI agents.
• Participate actively in Agile ceremonies including sprint planning, stand-ups, retrospectives, and backlog refinement to keep delivery on track.
• Surface and mitigate quality risks before they escalate, proactively communicating test coverage gaps, flagging scope concerns during planning, and helping the team maintain quality commitments.
• Own the test strategy and automation architecture with data quality as the primary focus, spanning ETL/ELT pipeline validation, source-to-target reconciliation, functional, end-to-end (Playwright), BDD, and performance (JMeter) layers.
• Build and maintain robust Python-based test frameworks and BDD feature suites, including reusable SQL and pandas/PySpark assertion libraries for data comparison, profiling, and reconciliation, aligned to biopharma business requirements.
• Design and govern JMeter performance test plans covering both application and data layers, including pipeline throughput, load-window adherence, and large-volume query response; analyse results and drive remediation.
• Design data validation pipelines and complex SQL queries in PostgreSQL and Snowflake.
• Serve as the go-to QA engineer for the hardest test challenges involving complexity, regulatory risk, or system ambiguity.
• Produce clear test strategy documents, defect trend analyses, and quality reports for stakeholders; communicate quality status effectively to technical and non-technical audiences.
• Incorporate pharma manufacturer client needs and regulatory requirements into test coverage decisions; participate in incident responses and quality reviews with direct client impact.
• Apply strong analytical and problem-solving skills to diagnose complex test failures, anticipating system failure modes and designing proactive test coverage.
• Demonstrate full accountability for team-level quality outcomes, proactively managing risks and owning quality end-to-end.
• Lift the overall quality output of the team through proactive test design collaboration, knowledge sharing, and mentoring junior QA engineers.
• Stay current with the team's evolving test toolset including AI-augmented testing practices, Playwright updates, BDD patterns, and biopharma regulatory developments.
• Partner effectively across backend developers, UI/UX developers, product analysts, and domain stakeholders in a geographically distributed team.
• Evaluate and integrate AI-powered testing tools into the QA workflow.

Tech Stack

• Programming Languages: Python (pytest, pandas, PySpark)
• Automation Frameworks: Playwright (UI and API), Selenium WebDriver (legacy)
• Testing Methodologies: BDD (Gherkin, step libraries, living documentation), Manual testing
• Performance Testing: JMeter
• Databases: Snowflake, PostgreSQL, MySQL, RDS
• Data Validation: Complex SQL queries (joins, aggregations, window functions), ETL/ELT pipeline validation, data reconciliation
• CI/CD & Tools: Jira, Confluence, GitHub Copilot, Anthropic Claude Code, AWS Bedrock
• AI Tools: AI-augmented development and testing environments
• Other: Agile/Scrum, Git, API testing (Postman, Python requests)

5+ years of strong QA automation experience, expert Python skills (pytest, framework design), 3+ years of Playwright for UI/API testing, deep BDD expertise (Gherkin, step libraries), strong SQL (complex joins, window functions, Snowflake, Postgres), JMeter experience (good to have), hands-on with AI tools (Claude Code, Copilot, AWS Bedrock), Agile/Scrum, analytical problem-solving, mentoring skills.

Mission-driven work improving patients' lives, excellent and affordable medical benefits, Flexible Paid Time Off, robust Learning & Development opportunities with 700+ courses.