Automation Lead

PactFi•New York, NY

About The Position

Private asset markets (PE, Private Credit, VC, Real Estate) have 10x to 9.8T in AUM over the past decade and are projected to grow to $17T in the next five years. However, digital infrastructure has not kept pace, with most of the market operating predominantly in error-prone, internal-only software solutions. PactFi provides secure, end-to-end, operational infrastructure for managing complex private credit transactions. Our web-based application brings together all parties involved in such a transaction to more efficiently allocate capital, complete KYC, share documents, manage funds flow, and more. The platform is secured to a bank-grade standard, and we have received our SOC 2 Type 2 attestation. PactFi was developed in close partnership with two of the industry's largest players, both of whom represent the top 3 players in the private credit space by both size (AUM) and deal activity. Role Overview We are seeking an Automation Lead to own and scale our end-to-end test automation strategy. This role is both hands-on technical and strategic, requiring deep expertise in Playwright and a strong understanding of financial systems—particularly within private credit, lending, or capital markets workflows. You will define testing architecture, improve release confidence, and partner closely with engineering, product, and operations to ensure platform reliability in a high-stakes financial environment.

Requirements

5+ years in QA automation, SDET, or software engineering roles
Deep expertise with Playwright (required) in production environments
Strong proficiency in TypeScript/JavaScript
Experience designing scalable test frameworks from scratch
Solid understanding of CI/CD systems and modern DevOps practices
Experience testing API-driven architecture and distributed systems
Prior experience in fintech, capital markets, or lending platforms
Familiarity with concepts such as: Loan lifecycle & servicing Private credit structures Cash flow modeling & waterfalls Financial reporting & reconciliations

Nice To Haves

Experience with data validation pipelines (SQL, dbt, etc.)
Exposure to backend languages (Python, Java, or Go)
Experience with performance or load testing tools
Familiarity with cloud infrastructure (AWS, GCP)

Responsibilities

Automation Strategy & Leadership Own the design and evolution of the automated testing framework (primarily Playwright)
Establish best practices for E2E, integration, and regression testing
Drive test coverage across critical financial workflows (deal lifecycle, cash flows, reporting, etc.)
Mentor engineers and QA contributors; set standards for test quality and maintainability
Hands-On Engineering Build and maintain robust Playwright test suites (TypeScript/JavaScript)
Develop reusable testing utilities, fixtures, and CI/CD integrations
Implement parallelization, test isolation, and flakiness mitigation strategies
Integrate tests into CI pipelines (e.g., GitHub Actions, CircleCI)
Product & Domain Alignment Translate complex financial workflows (e.g., loan servicing, covenant tracking, capital calls) into deterministic test cases
Validate data integrity across systems (APIs, databases, reporting layers)
Collaborate with product and domain experts to identify edge cases and risk scenarios
Quality & Reliability Define SLAs for test reliability and pipeline performance
Monitor and improve test signal vs. noise
Introduce observability into testing (logs, traces, artifacts)
Lead incident retrospectives related to quality gaps
AI-Driven Testing & Development Implement and scale AI-assisted test case generation from product requirements, user stories, and production data
Leverage LLM-based tools to generate, refactor, and maintain Playwright test suites
Build workflows for automated test creation, prioritization, and gap detection using AI
Evaluate and integrate tools for self-healing tests, intelligent selectors, and failure triaging
Partner with engineering to incorporate AI into broader development workflows (code generation, debugging, QA automation)
Establish guardrails and validation strategies to ensure correctness and determinism in AI-generated tests