Position OverviewCiti's Wholesale Credit Risk (WCR) Technology organization is seeking a
Test Engineering Lead (Director, C15) to own and drive the quality engineering strategy for the
Helios platform - Citi's strategic credit risk management ecosystem spanning Credit Review, Credit Approvals, Collateral, Covenants, Helios Lynx, and related applications.
This is a hands-on, technically credible leadership role for an individual who can operate simultaneously as a
people leader of a global testing organization and as a
technical change agent who personally understands (and can demonstrate) modern test automation and emerging GenAI-driven testing approaches. The successful candidate will be the architect of Helios's transformation from a largely manual, high-touch regression model toward a highly automated, AI-augmented, continuously-testing operating model - directly improving speed-to-production, defect containment, and cost efficiency for one of Citi's most business-critical credit platforms.
This role will partner closely with Development, SRE, Product, and Business Analysis leads across the Helios program.
Business ContextHelios underpins Citi's Wholesale Credit Risk workflows - credit approvals, risk rating, collateral management, limits, and covenants - for institutional clients globally. As GenAI accelerates the pace and complexity of software change across the platform, the QE organization must scale test coverage and confidence
without a proportional increase in headcount. Current strategic priorities that this role will directly own or heavily influence include:
- Driving overall regression automation coverage toward and beyond a 90%+ automation target, up from a current baseline in the mid-to-high 80s.
- Reducing multi-day manual regression cycles (e.g., Helios Lynx, currently 5+ business days with 8-10 people) down to hours, through automation and parallelization on Citi's FAST test infrastructure.
- Standing up GenAI-enabled testing capabilities (e.g., agentic test authoring, AI-assisted defect triage, AI-generated test packs) as a core capability of the testing organization - not a side experiment.
- Reducing the manual test case backlog to fewer than 500 test cases.
- Improving defect containment - reducing UAT/production defect ratios, shortening average defect detection time, and systematically mapping production Problem tickets (PRBs) back into automated regression coverage to prevent recurrence.
- Leading the target-state operating model transition where automation engineering and E2E/governance functions are centralized under QE, while development teams take on greater ownership of SIT-level integration testing.
- Managing headcount, budget, and vendor/contractor transition (including offboarding of prior managed-service automation partners and scaling of a ring-fenced, global automation engineering team).
Key Responsibilities Global Team Leadership- Lead, mentor, and grow a global, cross-regional team of software testing professionals (SDETs, automation engineers, manual/functional testers, and test leads) spanning NAM, EMEA, and APAC.
- Define career paths, performance goals, and skills-uplift programs to shift the organization's skill mix from manual testing toward automation engineering and AI-augmented testing.
- Own headcount planning, budget management, and the transition from third-party managed testing services to a ring-fenced, sustainable internal/blended automation engineering team.
- Act as the senior QE voice in governance forums, steering committees, and Senior Technology Management reviews.
Test Automation Strategy & Execution- Own the end-to-end test automation roadmap for Helios, spanning API (Cucumber/Gherkin BDD), UI (Playwright/TypeScript, Selenium), and integration/E2E test suites, executed on Citi's FAST test infrastructure.
- Drive automation coverage from current levels toward the 90%+ target, systematically eliminating "manual only" and "manual pending" backlog categories.
- Establish and enforce test data management, environment stability, and production-representative test data strategies (including redacted production data refresh cycles) to eliminate flaky, low-confidence test results.
- Oversee migration and modernization of test management tooling (e.g., Zephyr to Octane) and reporting/dashboarding (FAST feature tag reporting, requirements coverage, regression dashboards).
GenAI & Testing Innovation - Agent of Change- Serve as the primary driver and evangelist for GenAI adoption within the testing lifecycle - including AI-assisted test case generation, AI-augmented code/test review (e.g., GitHub Copilot), agentic development platforms (e.g., Devin), and AI-powered QA workspaces (e.g., Stylus, Friday.ai).
- Define governance and quality guardrails for AI-generated test artifacts, ensuring all AI-authored tests are validated before being promoted into regression suites.
- Identify, pilot, and scale new GenAI-based testing solutions that measurably improve timeliness (faster regression cycles), quality (defect containment, reduced escapes to production), and cost (reduced manual effort and headcount intensity) of delivering software to production.
- Partner with Engineering, Architecture, and Citi's broader GenAI tooling teams to pull emerging capabilities into the Helios testing pipeline ahead of the broader organization.
Quality Engineering Governance & Metrics- Own quality KPIs and reporting cadence: automation coverage %, defect-to-story-point ratios, mean time to detect/resolve defects, regression pass rates, and production incident/problem trends tied back to test coverage gaps.
- Establish and maintain traceability between Agile requirements (Jira stories), automated test cases, and production Problem tickets (PRB-to-test-case mapping) to close testing blind spots systematically.
- Present testing health, risk, and roadmap progress to Senior Technology Management, Business, and Risk/Control stakeholders on a regular basis.
- Partner with SRE and Environment teams to ensure environment availability, stability, and capacity (including compute/ACU planning) support high-volume automated execution.
Stakeholder & Cross-Functional Partnership- Act as a trusted partner to Development leads, Product Owners, Business Analysts, and Site Reliability Engineering to embed quality earlier in the SDLC ("shift-left" testing).
- Collaborate with Testing Centers of Excellence (TCoE) and external advisory partners to benchmark practices and identify improvement opportunities.
- Represent the testing organization in the transition to a target operating model in which development teams increasingly own integration-level testing while QE focuses on E2E, governance, tooling, and automation engineering excellence.
Qualifications- 15+ years of relevant experience
- 12+ years of progressive experience in software testing, test automation, and software development, including significant hands-on technical experience (not purely managerial).
- 10+ years experience and proven track record leading global, multi-region testing/QE teams (onshore/offshore models), including managing both direct employees and vendor/contractor resources.
- 10+ years experience and demonstrated success driving large-scale test automation transformations - measurably increasing automation coverage, reducing regression cycle times, and reducing manual testing effort/backlog.
- Hands-on experience (current or recent) with modern test automation frameworks and approaches, such as:
- BDD frameworks: Cucumber/Gherkin
- UI/API automation: Playwright (TypeScript), Selenium
- Test management platforms: Zephyr, Octane, or equivalent enterprise test management tooling
- CI/CD and test execution infrastructure at scale (e.g., FAST or equivalent internal test-runner/dashboarding platforms)
- Direct experience piloting or scaling GenAI/AI-based tooling in a software development or testing context - e.g., AI-assisted test generation, AI code/test review copilots, agentic coding/testing platforms, or AI-powered defect triage - with the ability to speak credibly and technically to these solutions.
- Experience in financial services, capital markets, or credit risk technology strongly preferred; direct familiarity with Wholesale Credit Risk, credit approvals, collateral, or covenant management platforms is a plus.
- Experience managing defect/problem management processes, including root-cause analysis, defect taxonomy, and linking production incidents/problems (e.g., ServiceNow PRBs/INCs) back into test coverage.
Education- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical discipline required. BS or MS in Computer Science strongly preferred
Technical & Leadership Competencies- Technical depth: Must be able to engage credibly with engineers on architecture, code, automation frameworks, and AI tooling - this is not a purely managerial/administrative QE leadership role.
- Change leadership: A proven "agent of change" who can challenge legacy manual-first testing culture, build the case for investment, and execute transformation against resistance, budget constraints, and competing priorities.
- Data-driven management: Comfortable owning and presenting quality metrics/KPIs (automation %, defect ratios, pass rates, cycle times) to senior technology and business stakeholders.
- Global team leadership: Experience managing distributed, multicultural teams across time zones (NAM/EMEA/APAC), with strong communication and stakeholder management skills.
- Program/workstream management: Ability to structure, prioritize, and drive multiple concurrent workstreams (e.g., automation uplift, environment stability, tooling migration, headcount/budget planning, AI adoption) to defined outcomes and deadlines.
- Executive communication: Ability to present clearly and persuasively to Senior Technology Management and risk/control stakeholders, translating technical testing detail into business risk and value language.
Preferred (Nice to Have)- Prior experience in a regulated banking/financial institution technology environment, with familiarity with change management, controls, and audit expectations for testing evidence.
- Familiarity with cloud-native test environments (e.g., Red Hat OpenShift/ECS) and infrastructure-aware test planning (SIT/UAT environment capacity, compute allocation).
- Experience standing up or maturing a Testing Center of Excellence (TCoE) or equivalent quality governance function.
- Certifications in test automation, Agile/Scrum leadership, or AI/ML fundamentals.
Job Family Group: Technology
Job Family:Applications Development
Time Type:Full time
Primary Location:Irving Texas United States
Primary Location Full Time Salary Range:$170,000.00 - $300,000.00
In addition to salary, Citi's offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
Most Relevant Skills Please see the requirements listed above.
Other Relevant Skills Quality Assurance Testing, Selenium, Software Quality Assurance (SQA) Testing, Technology Leadership, Test Automation, Transformational Change, Zephyr for JIRA.
Anticipated Posting Close Date:Sep 27, 2026
Automated Processing and AIWe use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
