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Mumbai, Maharashtra, India
Onsite
Russell Investments is a leading outsourced financial partner and global investment solutions firm providing a wide range of investment capabilities to institutional investors, financial intermediaries, and individual investors around the world. Building on an 90-year legacy of continuous innovation to deliver exceptional value to clients, Russell Investments works every day to improve the financial security of its clients. The firm is “Top 12 Ranked Consultant (2009-2024)” in P&I survey 2024 with $964 billion in assets under advisement (as of December 31, 2025) and $381.8 billion in assets under management (as of March 31, 2026) for clients in 30 countries. Headquartered in Seattle, Washington in the United States, Russell Investments has offices around the world, including London, New York, Toronto, Sydney, Tokyo, Shanghai, and Mumbai.
Joining our Mumbai office means becoming part of a globally connected team where associates collaborate across functions, geographies, and time zones to support the work of a globally recognized asset management firm. Based in Goregaon (East), you will have the opportunity to work alongside colleagues around the world, contribute to meaningful initiatives, and build your career in a collaborative and inclusive environment. The Mumbai office operates with varying shifts to support collaboration across global time zones.
For more information, please visit https://www.russellinvestments.com.
We are seeking an accomplished Senior SDET II with 10-15 years of experience in quality engineering, test automation, AI-enabled testing, test management, and enterprise quality governance, ideally within the financial domain. This role requires a proven leader who can define testing strategy, architect enterprise-grade automation solutions, lead an Automation Center of Excellence (CoE), generate QA KPIs and status reporting, and drive quality-first practices across complex application ecosystems. You will collaborate with cross-functional teams to ensure secure, scalable, and reliable financial applications while championing innovation in automation, AI tools for testing, DevOps, and modern quality engineering methodologies.
Key Responsibilities
Lead quality engineering efforts across multiple agile teams and enterprise programs, influencing design, development, testing, and deployment strategies.
Define and enforce enterprise quality standards, test strategies, automation guidelines, release readiness criteria, and best practices across the organization.
Lead and mature the Automation Center of Excellence (CoE), including framework governance, reusable assets, automation standards, tool selection, and adoption roadmaps.
Architect and maintain enterprise-level test automation frameworks for web, API, mobile, backend, database, data integration, and batch systems.
Drive adoption of AI tools for testing, including AI-assisted test case generation, test data generation, self-healing automation, defect analysis, test maintenance, and risk-based testing.
Own end-to-end test management activities, including test planning, estimation, execution tracking, defect management, traceability, release sign-off support, and production readiness assessment.
Drive in-sprint automation, shift-left testing, CI/CD quality gates, and continuous testing practices to accelerate release cycles, Increased scope/test coverage and reduce defect leakage.
Collaborate with product owners, architects, engineering leads, DevOps, business stakeholders, and vendors to align testing with business priorities and delivery commitments.
Perform and oversee advanced functional, regression, integration, API, performance, security, accessibility, and data validation testing.
Ensure end-to-end test coverage across UI, API, database, services, integrations, and downstream systems.
Mentor and coach SDETs and QA engineers, fostering a culture of engineering excellence, continuous learning, and quality ownership.
Champion innovation in automation tools, AI-enabled testing, CI/CD pipelines, observability, DevOps, and modern quality engineering practices.
QA KPI Generation, Governance & Status Reporting
Define, generate, and maintain enterprise QA KPIs, quality metrics, automation metrics, and release health indicators.
Create and publish QA dashboards and status reports for leadership, including testing progress, defect trends, risks, blockers, environment health, and release confidence.
Track and report key metrics such as automation coverage, test execution progress, pass/fail trends, defect density, defect leakage, defect aging, escaped defects, test case effectiveness, requirements traceability, automation ROI, sprint quality, and CI/CD quality gate compliance.
Provide weekly and monthly status reporting across portfolios, programs, releases, and agile teams with clear commentary on quality risks and mitigation plans.
Analyze QA metrics to identify quality gaps, engineering bottlenecks, regression risk, automation maintenance needs, and opportunities for continuous improvement.
Present quality dashboards, automation adoption, release readiness, and strategic recommendations to technology leaders, business stakeholders, and program governance forums.
Required Skills & Experience
10-15 years of experience in software testing, quality engineering, test automation, and test management, with significant exposure to financial systems.
Strong programming expertise in C#, Python, or Java.
Hands-on experience with modern automation tools such as Selenium, Playwright, Cypress, and Appium.
Advanced API testing and automation skills using Postman, REST Assured, Karate, or similar tools.
Deep knowledge of CI/CD pipelines and DevOps tooling such as Jenkins, TeamCity, GitHub Actions, and Azure DevOps.
Strong SQL and database validation skills for financial domain, reporting flows, and data reconciliation. Good to have exposure on Snowflake, DBT, Fivetran etc.
Experience with test management and defect management tools such as Jira, Azure DevOps, Xray, Zephyr, ALM, or equivalent platforms.
Experience generating QA KPIs, executive dashboards, release status reports, and quality trend analysis using tools such as Power BI, Excel, Jira dashboards, or Azure DevOps analytics.
Exposure to Salesforce, Adobe AEM, cloud platforms, data platforms, or similar enterprise systems preferred.
Experience with performance testing tools such as JMeter, LoadRunner, or k6 is a plus.
Hands-on experience or strong exposure to AI-based test automation solutions and AI-assisted engineering tools is required.
AI Testing & Automation CoE Experience
Experience evaluating and adopting AI tools for testing, automation development, test design, defect triage, test data creation, and automation maintenance.
Hands-on exposure to tools and platforms such as GitHub Copilot, Microsoft Copilot, OpenAI/Azure OpenAI, Cursor, ACCELQ AI, KaneAI, Testim, Functionize, Mabl, or similar AI-enabled testing solutions.
Ability to define responsible AI usage guidelines for testing, including security, privacy, data protection, accuracy checks, and human review controls.
Experience leading automation framework standardization, code review practices, reusable libraries, reporting utilities, and automation maturity assessments through an Automation CoE.
Ability to measure and communicate automation value through adoption metrics, ROI, maintenance reduction, regression efficiency, and release acceleration.
Candidate Requirements
Proven ability to lead QA/SDET teams, Automation CoE initiatives, and quality engineering workstreams for enterprise projects.
Strong understanding of SDLC, Agile, DevOps, CI/CD, test management, and modern quality engineering practices.
Ability to design testing strategy for large-scale applications, enterprise programs, and cross-platform ecosystems.
Ability to design automation solutions at scale, ensuring maintainability, reusability, observability, and alignment with enterprise standards.
Excellent troubleshooting skills and ability to manage multiple projects, releases, and stakeholders simultaneously.
Strong stakeholder management skills with the ability to influence prioritization of quality, automation, technical debt, and risk mitigation initiatives.
Ability to proactively provide accurate QA KPI reporting, release status reporting, risk reporting, and executive-level quality updates.
Soft Skills & Core Values
Exceptional communication and leadership skills with clear, concise reporting.
Ownership mindset with accountability for quality outcomes and release confidence.
Ability to thrive in a fast-paced, agile, and enterprise delivery environment.
Proactive problem-solving, decision-making, and innovation mindset.
Strong mentoring, coaching, collaboration, and stakeholder engagement skills.
Commitment to integrity, continuous learning, responsible AI adoption, and engineering excellence.
Preferred Qualifications
Bachelor's or master's degree in Computer Science, Information Technology, Engineering, or related field.
Certifications in test automation, cloud technologies, Agile methodologies, AI, DevOps, or quality engineering are a plus.
Experience in investment management, wealth management, capital markets, banking, or other financial services environments is preferred.
Experience leading enterprise quality transformation, Automation CoE setup, QA governance, or AI-enabled testing adoption is highly desirable.