QA Engineer

Role Context

We are looking for a talented Quality Engineer to join our AI Services team. You'll help Aflac use AI to modernise its longest-running core systems, and you'll own the question that matters most: how do we prove nothing broke?

This is not a traditional testing role. You will champion quality across the entire software development lifecycle, from discovery and planning through to production. You will combine hands on testing expertise with modern quality engineering practices, AI assisted tooling, automation, evaluation, and coaching.

Two kinds of quality matter here. The first is the software we produce: modern services that must behave exactly like the systems they replace. The second is the AI that produces it. Our engineers use AI agents to analyse, build, and test code. Those agents are non-deterministic, so you'll help define how we evaluate them, put guardrails around them, and prove they are reliable.

Working closely with AI Native Software Engineers, Architects, Security, domain experts and partner teams, you will define the quality strategies, evaluation frameworks and engineering standards that let us modernise at scale with confidence.

The Team

The AI Services team helps transform how Aflac uses AI at scale where it matters. Taking priority use cases from concept to production, proving what works early, and packaging the results so other teams can repeat them. This team leads Aflac's AI harness engineering methodology, equipping engineers and product teams with AI driven workflows and setting SDLC standards that make AI available, safe and scalable.

One of our current priorities is modernising some of Aflac's longest running core systems. Using Aflac's AI harness engineering methodology, AI Services will support the delivery teams by shaping the methods and patterns that turn legacy code into robust, testable modern services. Every pass records the issues found and feeds them back into the next one. Over time, each migration needs less manual fixing.

AI Services Engineering operates as two functions. This role sits in the Context Engineering function, taking AI native products from concept to production and setting the AI harness engineering methodology behind them. The other function is AI Platform, owning the Agentic Platform: how Aflac runs agents at scale, cost efficiently and securely, with the right risk posture and robust operational controls. Alongside both sit AI Enablement, driving adoption, education and communication across the business. Two sides of one engineering team, working closely with the full AI Services team. You'll work with AI Native Software Engineers to build quality into the harness and every service it produces, and with AI Platform, Solution Architects, Enterprise Architecture, Security and domain experts in an agile environment.

Key Responsibilities

Modernisation Quality

• Own the quality strategy for each capability being modernised, from discovery through to go live
• Design comparison testing that runs today's system and the new build on the same scenarios and proves they match
• Independently verify each build, filing defects against evidence rather than fixing them in place
• Define and enforce exact match standards for financial and regulatory outcomes, with no tolerance
• Plan and run parallel runs, period end checks and rehearsed rollback before any capability goes live
• Build test data and scenario libraries that cover real business modes, record types and edge cases
• Participate in system integration testing across multiple products, services and global teams

AI Native Engineering and Evaluation

• Define evaluation frameworks for the AI harness, including accuracy baselines, regression suites and quality metrics for agent output
• Test agentic and AI systems for non-deterministic behaviour, guardrail effectiveness, prompt injection and safe failure
• Track the issues found on every harness pass and turn them into checks that stop the same defect returning
• Help define automated quality gates covering coverage, code quality, security and behavioural evidence
• Use AI assisted engineering tools to accelerate test design, automation, test data generation and exploratory testing
• Review AI generated tests and code with a critical eye, and know when to trust them

Quality Leadership

• Develop risk-based test approaches that balance customer impact, business value, complexity and delivery timelines
• Contribute to automated tests and CI/CD quality controls that support continuous delivery
• Facilitate example mapping and quality focused discovery to improve requirements and shared understanding
• Coach engineers on testability, automation and defect prevention, and promote shared ownership of quality
• Partner with Security, Architecture and Engineering to meet security, privacy, compliance and governance requirements
• Contribute to the evolution of engineering standards, testing practices and quality frameworks across the organisation

Skills and experience

Below is an overview of the skills and experience we are looking for, but remember, don't rule yourself out if you don't have everything on the list. It's your curiosity and your attitude we are really after.

Essential

• 5+ years of experience in software quality engineering, software testing or software development
• Experience defining and executing testing strategies for complex web, cloud or distributed systems
• Strong experience with Playwright, Robot Framework or equivalent automation tools
• Experience building and maintaining automated tests within CI/CD pipelines
• Experience using AI assisted engineering tools to improve testing effectiveness and productivity
• Experience testing data heavy or financial systems where accuracy is critical
• Strong understanding of Agile delivery and DevOps practices
• Understanding of security, privacy, compliance and governance requirements
• Excellent communication and coaching skills
• Candidates must be based in Northern Ireland with the relevant Right to Work visa

Desirable

• Experience testing AI enabled applications, agentic systems or intelligent workflows
• Experience defining AI evaluation frameworks, accuracy baselines and quality metrics
• Experience with legacy migration, data reconciliation or parallel run testing
• Exposure to mainframe technologies such as COBOL, JCL or batch processing
• Experience with Java, AWS and cloud native technologies
• Experience with event driven systems and messaging platforms (e.g. Kafka)
• Experience with observability, monitoring and diagnostics tools
• Insurance domain expertise, such as experience with policy administration, claims or billing systems

So that's us. Thanks for taking the time to read this far. We look forward to hearing from you if you fancy joining an innovative tech company that runs locally but is supported by a well established, highly recognised Fortune 500 company in the US.

Aflac Northern Ireland is an equal opportunities employer.