Senior/Lead QA Engineer (Auto & Manual, in-house product)

VeryPay is a leading fintech Technology Service Provider (TSP) delivering secure, NFC-based payment authorization infrastructure across multiple verticals – including cashless schools, retail, social cash transfers, transportation, and healthcare. Our platform processes millions of transactions via closed-loop ledger systems, integrating with Mobile Money Operators (MMOs) such as MTN, and spanning card lifecycle management (Mifare NFC), HSM-backed cryptography, and microservices-based cloud architecture.

We are building the next generation of our platform – a full migration from monolithic to microservices architecture – and are looking for a Senior QA Engineer who can grow with us.

Job 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: you will define the test architecture, drive automation investment, champion quality culture across engineering, and 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.

Test Strategy & Execution

• Design end-to-end test strategies covering functional, integration, regression, performance, and security test layers across web, mobile, and backend services.
• Build and maintain robust manual and automated test suites for NFC transaction flows, card lifecycle operations, wallet movements, and MMO integrations.
• Ensure test coverage spans microservice boundaries (user, merchant, device, wallet, product, transaction, card services) including contract and integration testing at API gateways.
• 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.
• Validate multi-tenant isolation: ensure that organisation, school, merchant, and agent tenant configurations produce correct, independent behavior without data leakage or cross-tenant interference.

AI-Assisted Testing

• 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.
• Use AI-based log analysis and anomaly detection to proactively identify quality risks across CI/CD pipelines.
• Design prompts and workflows for AI-assisted exploratory testing, including structured test scenario generation from product specifications and API schemas.
• 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.

Fintech & Payment-Specific QA

• Test NFC card transaction authorization flows, offline payment scenarios, and deferred HSM verification paths.
• Validate double-entry ledger integrity, OVA (Open Value Account) balance consistency, and fund movement operations (Top-up, Payment, Funds In/Out).
• Perform security-focused testing on payment token flows, JWT-based Partner API authentication (HS256 / ES256), and PCI-relevant data handling.
• Collaborate with the HSM and cryptographic infrastructure teams to define and validate key injection, PIN encryption (scenarios A-D), and card personalization test cases.

Production Support & Issue Verification

• Serve as the QA point of contact for production incidents – reproduce reported issues in staging, confirm root cause, and verify fixes before re-deployment.
• 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.
• Analyse production logs, monitoring dashboards (Prometheus, Grafana, ELK), and transaction traces to identify quality signals and prevent recurrence.
• Maintain a living production issue register to track defect patterns, recurrence rate, and long-term remediation actions.

Coordination with Development & Product Teams

• Partner with product managers to translate feature requirements and acceptance criteria into testable specifications before development begins – enforcing a shift-left quality model.
• 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.
• Facilitate structured QA handoff processes: definition of done checklists, pre-release sign-off gates, and cross-team readiness reviews before each deployment.
• Maintain open communication channels with development and product teams on active defects, test progress, and release readiness – ensuring no quality risks are surfaced late.
• Own the overall QA strategy for VeryPay’s platform – define standards, tooling decisions, and quality processes across the engineering team.
• Lead, mentor, and grow a QA team (currently junior/mid engineers); conduct structured 1:1s, performance feedback, and skills development planning.
• Drive test architecture decisions: framework selection, test pyramid balance, toolchain standardization, and technical debt management within the QA layer.
• Act as the QA representative in sprint planning, architecture reviews, and cross-team technical discussions – advocating for quality requirements from inception.
• Build a quality culture across the broader engineering team, not just within QA – through pairing, documentation, and shift-left practices.

Quality Process & Reporting

• Implement and maintain quality gates in CI/CD pipelines (GitHub Actions, Jenkins, or equivalent) including automated regression on every merge to main.
• Define and track QA KPIs: defect escape rate, test coverage, automation ratio, mean time to detect (MTTD) – report to engineering leadership with actionable insights.
• Own incident post-mortems from the quality perspective: root cause analysis, regression gap identification, and process improvement actions.
• Collaborate cross-functionally with product managers, backend engineers, DevOps, and integration partners to embed quality requirements early in the development lifecycle.

Qualifications

Core QA Expertise

• 5+ years of software QA experience with proven ownership of both manual and automated testing on production-grade systems.
• Strong hands-on experience with test automation frameworks: Selenium, Appium, Playwright, Cypress, or equivalent.
• Expertise in API testing (REST/JSON) using tools such as Postman, RestAssured, or Karate.
• Experience designing test strategies for microservices architectures, including contract testing (Pact or equivalent) and service mesh validation.
• Proficiency in at least one scripting language: Python, JavaScript/TypeScript, or Java, for test framework development.

AI Tooling Proficiency

• Hands-on experience with at least one AI-assisted testing or development tool (GitHub Copilot, Cursor, Testim, Mabl, Applitools, or similar).
• Demonstrated ability to use LLMs (e.g., Claude, GPT-4) to generate test plans, identify edge cases, and review test coverage against specifications.
• 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).

QA Leadership

• Demonstrated experience leading or managing a QA team — setting direction, mentoring engineers, and owning quality outcomes end-to-end.
• Ability to define and evolve a QA strategy aligned with product roadmap and engineering capacity — balancing automation investment, manual coverage, and risk tolerance.
• Experience driving QA KPI frameworks: defect escape rate, automation coverage ratios, test flakiness reduction, and release confidence metrics.
• Proven track record of cross-functional influence — able to negotiate quality requirements with product and engineering stakeholders without formal authority.

Process & Collaboration

• Fluency in Agile/Scrum environments with direct experience integrating test automation into CI/CD pipelines.
• Strong analytical and troubleshooting skills with the ability to isolate defects across distributed, asynchronous service architectures.
• Excellent communication skills; able to translate complex technical QA findings into clear risk summaries for non-technical stakeholders.

Preferred Skills:

• Direct experience in the payments industry – knowledge of payment gateways, Mobile Money APIs, wallet systems, or card-present transaction flows.
• Familiarity with NFC/Mifare card technology, HSM operations, or cryptographic key management concepts.
• Experience with performance and load testing tools: JMeter, k6, Gatling, or LoadRunner.
• Security testing experience (OWASP, SAST/DAST tooling, penetration testing awareness) especially in a PCI or financial services context.
• Experience with Kubernetes-based environments and observability tooling (Prometheus, Grafana, ELK) for QA validation and monitoring.
• Prior experience mentoring junior QA engineers or leading a QA sub-team.

Additional Information

AI at VeryPay

VeryPay takes a thoughtful, security-conscious approach to AI adoption. We actively expand AI tooling across engineering workflows — from AI-assisted code review and spec-to-code generation, to intelligent test coverage analysis.

At the same time, we apply strict controls: AI is never used in direct cryptographic operations, HSM interactions, or payment authorization logic. We expect this engineer to understand and respect this boundary — and to help us build the right guardrails as our AI tooling matures.

What We Offer

• Work on a technically challenging, real-world fintech platform used for social cash transfers, cashless schools, and enterprise retail payments across Africa.
• A team that treats quality engineering as first-class — with investment in tooling, process, and automation.
• Active investment in AI-augmented development workflows with a pragmatic, safety-first philosophy.
• Competitive compensation commensurate with experience and location.
• 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.