Director Test Engineering Lead Wholesale Credit Risk Technology

Worky; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

Citi’s Wholesale Credit Risk Technology organization seeks a Test Engineering Lead to own the quality engineering strategy for the Helios platform, a broad suite of credit risk applications. This role combines global people leadership with hands-on, AI-driven testing modernization to improve speed-to-production and defect containment.

You will partner with Development, SRE, Product, and Business Analysis across the Helios program while guiding automation, test data, and environment strategies.

Qualifications

• Senior leadership experience in software testing and QE
• Proven ability to drive automation strategy across global teams
• Experience with GenAI-powered testing approaches and governance
• Ability to partner with Development, SRE, Product, and BA leads

Responsibilities

• Own end-to-end QA strategy for Helios platform and related apps
• Lead a global testing organization and manage budget/headcount
• Drive 90%+ automation target and reduce regression timelines
• Introduce GenAI-enabled testing capabilities and governance
• Oversee tooling migrations (Zephyr to Octane) and reporting dashboards
• Collaborate with cross-functional partners to accelerate delivery and quality

Skills

Global team leadership

Test automation strategy

GenAI in testing

Stakeholder collaboration

Tools

Playwright

Selenium

Cucumber/Gherkin

Octane

Zephyr

FAST

Devin

Stylus

Friday.ai

Job description

Position Overview

Citi'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 Context

Helios 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).

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