About us

ace is a specialist post-digital advisory and delivery partner helping financial institutions implement high-impact automation, AI, and post-digital solutions in regulated environments. We combine deep technical expertise with a practical understanding of governance, controls, and operational risk to deliver production-grade outcomes at pace.

We are part of the G MASS group, a global financial services resource augmentation and consulting firm that provides expert talent and delivery support across transformation, change, and operational resilience.

QA Automation Engineer

ace has partnered with a prestigious, leading global Hedge Fund to appoint an experienced QA Automation Engineer to take hands-on ownership of the build-out and enterprise adoption of the firm’s in-house automated testing platform.

This is an engineering-first role. You will be the senior technical voice on it: developing across the full stack, extending its intelligence and integrations, and driving it toward a fully automated, agent-orchestrated and ultimately predictive testing capability. The target state is complete lineage from requirement through to result, governed and auditable end to end, with no part of the process running out of spreadsheets.

You will work with a high degree of autonomy alongside a small, highly efficient QA function, in a demanding and fast-moving environment where the expectation is delivery rather than management overhead.

Please note that this role requires presence in the client’s London office five days per week. This is non-negotiable.

Responsibilities

Platform engineering and delivery

• Take hands-on ownership of the continued build-out of the in-house automated testing platform, driving it from partial implementation to full adoption across the applications in scope.
• Develop across the full stack: front-end interfaces in React and JavaScript, and back-end services, automation logic and data processing in Python.
• Extend the platform interface so that test design, execution, evidence capture, results and stakeholder packaging all sit in a single pane, removing residual spreadsheet-based working.
• Build and maintain integrations across the surrounding toolchain, requirements management, source control and pull-request data, and positions and transactions data, so that test coverage is derived systematically rather than assembled manually.
• Maintain integration with the firm’s enterprise design system so that changes to UI design are automatically assessed for regression impact on dependent applications.

Lineage, governance and assurance

• Deliver complete lineage from requirement, through rule and rule change, to test script, execution, results and UAT packaging - with full auditability, governance and versioning at every step.
• Extend the platform’s use of AI to interpret requirements, distinguish well-formed from poorly-formed requirements, identify coverage gaps, and generate candidate test scripts and expected results.
• Build out the automation catalogue, including intelligent reconciliation across positions and transactions, so that the downstream impact of new or amended logic can be assessed systematically at instrument and transaction level.
• Design and implement entitlements and access controls within the platform, including for agent-based execution, ensuring no test process can reach or surface data outside its permitted scope.

Infrastructure, CI/CD and engineering standards

• Own the platform’s infrastructure and deployment pipeline, managing environments through a code-first, infrastructure-as-code approach.
• Apply production-grade engineering practice throughout: version control and branching discipline, code review, automated regression, monitoring and repeatable release processes.

Product direction and technical leadership

• Translate an established product vision into deliverable architecture, working independently and escalating by exception.
• Shape the roadmap toward agent-orchestrated and predictive testing, including how individual agents are scoped, governed and coordinated where a single test scenario spans several of them.
• Support integration with adjacent enterprise tooling as the wider ecosystem develops.
• Mentor and upskill an incumbent QA function whose background is predominantly manual testing, raising the automation capability of the team as a whole

Requirements

• Financial services experience is essential, and hedge fund exposure is welcome but not required.
• Strong, current, hands-on full-stack engineering experience with a specialism in test automation.
• Front end: React and JavaScript, to a standard sufficient to build and maintain production interfaces.
• Back end: Python, for automation logic, service development and data manipulation.
• CI/CD and infrastructure: demonstrable experience with GCP and Terraform, and with managing infrastructure as code.
• Engineering discipline: Git and version control, branching strategies, pull-request workflows, and model and artefact repositories.
• Practical familiarity with AI and machine-learning tooling applied to real delivery problems, for example requirement interpretation, test generation and gap analysis, with a clear view on controls, traceability and auditability.
• A track record of taking automation to genuine production adoption and owning it thereafter, rather than delivering proofs of concept.
• Ability to operate independently and at pace in a demanding, high-performance environment, making day-to-day implementation decisions without direction.
• Strong problem-solving ability and conceptual range.

Benefits

• Initial 12-month contract.
• Start date: mid to late August 2026.
• Rate dependent on experience.
• Five days per week in the client’s London office (non-negotiable).
• High-visibility ownership of a platform with rapidly growing enterprise adoption, and a clear mandate to shape its direction.