Role Description
The Senior QA Engineer / QA Lead will own VeryPay's end-to-end quality strategy — leading the QA function, mentoring the team, and ensuring our platform meets the highest standards of correctness, reliability, and security before every release. This role combines hands-on technical depth with team leadership:
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Define the test architecture.
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Drive automation investment.
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Champion quality culture across engineering.
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Act as the primary quality voice in cross-functional discussions.
This role requires someone who can pair deep technical QA expertise with practical knowledge of AI-assisted testing workflows — from intelligent test generation to autonomous regression coverage.
Qualifications
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5+ years of software QA experience with proven ownership of both manual and automated testing on production-grade systems.
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Strong hands-on experience with test automation frameworks: Selenium, Appium, Playwright, Cypress, or equivalent.
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Expertise in API testing (REST/JSON) using tools such as Postman, RestAssured, or Karate.
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Experience designing test strategies for microservices architectures, including contract testing (Pact or equivalent) and service mesh validation.
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Proficiency in at least one scripting language: Python, JavaScript/TypeScript, or Java, for test framework development.
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Hands-on experience with at least one AI-assisted testing or development tool (GitHub Copilot, Cursor, Testim, Mabl, Applitools, or similar).
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Demonstrated ability to use LLMs (e.g., Claude, GPT-4) to generate test plans, identify edge cases, and review test coverage against specifications.
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Understanding of where AI augmentation is appropriate in a QA workflow and where it must be restricted (e.g., never in direct HSM or cryptographic validation paths).
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Demonstrated experience leading or managing a QA team — setting direction, mentoring engineers, and owning quality outcomes end-to-end.
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Ability to define and evolve a QA strategy aligned with product roadmap and engineering capacity — balancing automation investment, manual coverage, and risk tolerance.
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Experience driving QA KPI frameworks: defect escape rate, automation coverage ratios, test flakiness reduction, and release confidence metrics.
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Proven track record of cross-functional influence — able to negotiate quality requirements with product and engineering stakeholders without formal authority.
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Fluency in Agile/Scrum environments with direct experience integrating test automation into CI/CD pipelines.
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Strong analytical and troubleshooting skills with the ability to isolate defects across distributed, asynchronous service architectures.
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Excellent communication skills; able to translate complex technical QA findings into clear risk summaries for non-technical stakeholders.
Requirements
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Design end-to-end test strategies covering functional, integration, regression, performance, and security test layers across web, mobile, and backend services.
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Build and maintain robust manual and automated test suites for NFC transaction flows, card lifecycle operations, wallet movements, and MMO integrations.
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Ensure test coverage spans microservice boundaries (user, merchant, device, wallet, product, transaction, card services) including contract and integration testing at API gateways.
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Design and execute multi-device test scenarios covering POS terminals, NFC card readers, mobile apps, and USSD channels - validating consistent behavior across hardware variants and OS versions.
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Validate multi-tenant isolation: ensure that organisation, school, merchant, and agent tenant configurations produce correct, independent behavior without data leakage or cross-tenant interference.
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Leverage AI tools (e.g., GitHub Copilot, Testim, Mabl, or equivalent LLM-assisted frameworks) to accelerate test case generation, coverage gap analysis, and regression suite maintenance.
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Use AI-based log analysis and anomaly detection to proactively identify quality risks across CI/CD pipelines.
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Design prompts and workflows for AI-assisted exploratory testing, including structured test scenario generation from product specifications and API schemas.
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Stay current on evolving AI testing tooling and champion adoption of practical, secure AI workflows within the QA function - with appropriate caution in sensitive cryptographic and payment-critical paths.
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Test NFC card transaction authorization flows, offline payment scenarios, and deferred HSM verification paths.
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Validate double-entry ledger integrity, OVA (Open Value Account) balance consistency, and fund movement operations (Top-up, Payment, Funds In/Out).
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Perform security-focused testing on payment token flows, JWT-based Partner API authentication (HS256 / ES256), and PCI-relevant data handling.
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Collaborate with the HSM and cryptographic infrastructure teams to define and validate key injection, PIN encryption (scenarios A-D), and card personalization test cases.
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Serve as the QA point of contact for production incidents - reproduce reported issues in staging, confirm root cause, and verify fixes before re-deployment.
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Maintain a structured hotfix verification workflow: fast-track regression scope, execute targeted smoke and regression suites, and provide go/no-go sign-off under time pressure.
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Analyse production logs, monitoring dashboards (Prometheus, Grafana, ELK), and transaction traces to identify quality signals and prevent recurrence.
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Maintain a living production issue register to track defect patterns, recurrence rate, and long-term remediation actions.
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Partner with product managers to translate feature requirements and acceptance criteria into testable specifications before development begins - enforcing a shift-left quality model.
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Work directly with backend and frontend engineers during development cycles: review design documents for testability, participate in code reviews, and provide early QA feedback on pull requests.
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Facilitate structured QA handoff processes: definition of done checklists, pre-release sign-off gates, and cross-team readiness reviews before each deployment.
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Maintain open communication channels with development and product teams on active defects, test progress, and release readiness - ensuring no quality risks are surfaced late.
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Own the overall QA strategy for VeryPay's platform - define standards, tooling decisions, and quality processes across the engineering team.
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Lead, mentor, and grow a QA team (currently junior/mid engineers); conduct structured 1:1s, performance feedback, and skills development planning.
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Drive test architecture decisions: framework selection, test pyramid balance, toolchain standardization, and technical debt management within the QA layer.
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Act as the QA representative in sprint planning, architecture reviews, and cross-team technical discussions - advocating for quality requirements from inception.
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Build a quality culture across the broader engineering team, not just within QA - through pairing, documentation, and shift-left practices.
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Implement and maintain quality gates in CI/CD pipelines (GitHub Actions, Jenkins, or equivalent) including automated regression on every merge to main.
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Define and track QA KPIs: defect escape rate, test coverage, automation ratio, mean time to detect (MTTD) - report to engineering leadership with actionable insights.
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Own incident post-mortems from the quality perspective: root cause analysis, regression gap identification, and process improvement actions.
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Collaborate cross-functionally with product managers, backend engineers, DevOps, and integration partners to embed quality requirements early in the development lifecycle.
Benefits
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Work on a technically challenging, real-world fintech platform used for social cash transfers, cashless schools, and enterprise retail payments across Africa.
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A team that treats quality engineering as first-class — with investment in tooling, process, and automation.
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Active investment in AI-augmented development workflows with a pragmatic, safety-first philosophy.
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Competitive compensation commensurate with experience and location.
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Flexible remote-first work environment with a collaborative, async-friendly engineering culture.
How to Apply
Send your CV and a brief cover note. In your cover note, please address: (1) a testing challenge you solved in a payment or financial system, and (2) how you have used or would use AI tools to improve test coverage or efficiency.
