About the role
As a Program Manager - AI-Driven Quality Engineering Transformation (Life Insurance), you will make an impact by driving large-scale Quality Engineering transformation initiatives and accelerating the adoption of AI-driven testing practices across complex enterprise environments. You will be a valued member of the Quality Engineering organization and work collaboratively with engineering, product, architecture, delivery, and business stakeholders to modernize software quality and delivery outcomes.
In this role, you will:
• Lead enterprise-wide Quality Engineering transformation programs, defining strategy, roadmaps, governance models, and measurable business outcomes.
• Drive the adoption of Generative AI and Agentic AI solutions across the Software Testing Lifecycle (STLC) to improve productivity, quality, and speed-to-market.
• Partner with cross-functional teams to manage complex program delivery, align stakeholders, mitigate risks, and ensure successful execution of strategic initiatives.
• Champion modern Quality Engineering practices including shift-left testing, CI/CD integration, DevOps, test observability, quality engineering metrics, and intelligent automation.
• Foster a culture of innovation by evaluating emerging AI technologies, developing accelerators and prototypes, and promoting AI-first engineering practices across teams.
Work model: Hybrid
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring 2-3 days per week in a client or Cognizant office in Boston, MA. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
What you need to have to be considered
• 20+ years of experience in Quality Engineering, Test Architecture, Test Automation, and enterprise-scale testing transformation programs.
• Proven success defining and executing QE strategies, automation roadmaps, governance frameworks, and quality transformation initiatives across globally distributed teams.
• Hands-on expertise with Generative AI and Agentic AI technologies, including Prompt Engineering, RAG, AI-powered test automation, intelligent test design, and predictive quality analytics.
• Strong knowledge of modern Quality Engineering practices including shift-left testing, DevOps, CI/CD, test observability, quality metrics, environment management, test data management, UAT coordination, and release readiness.
• Technical expertise in Python, Java, Selenium, Playwright, API Automation, and scalable automation framework development.
• Experience managing complex cross-functional programs, stakeholder engagement, dependency management, and enterprise risk mitigation.
• Strong understanding of AI platforms and frameworks such as Azure OpenAI, LangChain, LangGraph, Semantic Kernel, GitHub Copilot, Claude, MCP, and related AI orchestration technologies.
These will help you stand out
• Domain expertise in Life Insurance and Annuities, including policy administration, claims, underwriting, billing, and digital transformation programs.
• Experience building AI-powered testing accelerators, autonomous testing agents, conversational QE assistants, and intelligent release validation solutions.
• Demonstrated thought leadership in AI adoption, responsible AI governance, and value realization strategies.
• Proven ability to influence executive stakeholders and serve as a trusted advisor for enterprise transformation initiatives.
• Experience leading innovation programs that improve engineering effectiveness, reduce costs, and enhance software quality outcomes.
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
Salary and Other Compensation:
Applications will be accepted until September 04, 2026.
The annual salary for this position is between $96,750– $153,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits:
Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
Medical/Dental/Vision/Life Insurance
Paid holidays plus Paid Time Off
401(k) plan and contributions
Long-term/Short-term Disability
Paid Parental Leave
Employee Stock Purchase Plan
Cognizant will only consider applicants for this position who are legally authorized to work in the United States without company sponsorship.
*Please note, this role is not able to offer visa transfer or sponsorship now or in the future*
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
