Manager, Quality Engineering

Job description
The Role

We are looking for a Senior QA Engineering Lead who thinks like a product engineer, operates like a data scientist, and leads like a builder. This is not a traditional test

management role. This is a pivotal, senior leadership position within InvestCloud’s Digital Wealth product and technology group — responsible for transforming quality engineering from a gate at the end of the pipeline into an intelligent, continuous capability woven across every stage of the product delivery lifecycle (PDLC). You will lead a team of QA engineers while being deeply hands-on yourself — designing automation frameworks, embedding AI-driven quality intelligence, and setting the quality

engineering standard for one of the most complex, high-stakes product suites in the wealth management technology space.

You will work in close partnership with engineering, product, platform, data, and operations teams — driving a culture where quality is everyone’s responsibility and AI is

the accelerator.

What You Will Own
• End-to-End Quality Strategy Across the PDLC
• Define and own the quality engineering roadmap for Digital Wealth — from

requirements and design through development, integration, release, and production
• Embed quality gates at every stage of the PDLC — shifting left to catch defects at design time, not post-release
• Lead the evolution from manual, reactive testing to a predictive, AI-augmented quality model across all Digital Wealth product lines
• Own the release confidence framework — Go/NoGo criteria, coverage thresholds,risk-based testing models, and rollback decision logic
• Intelligent Test Automation & AI Enablement
• Architect and own a modern test automation platform — functional, regression, API, performance, and BDD — integrated with CI/CD pipelines (GitLab)
• Drive adoption of AI-powered QA tooling including: o AI test case generation from requirements (natural language → test suite)o Automated test taxonomy mapping and Jira classification (coverage gaps surfaced automatically) o Defect impact analysis — identifying which platform tiers, portals, andregression flows are affected by every fix o AI-assisted environment health monitoring — proactive alerting with module-level root-cause hints o AI-driven release notes and Go/NoGo documentation generated from live Jira + GitLab data
• Champion test data management at scale — including AI-generated schema validated test datasets for complex scenario permutations (account × model × sleeve × restriction × security)
• Integrate AI observability into QA — log analysis, anomaly detection, and predictive failure identification across Dev, SIT, CERT, and Production

environments
• Quality Engineering Leadership & Team Development
• Build, lead, and mentor a high-performing team of Quality Engineers and SDET engineers.
• Shift the team identity from “testers” to Quality Engineers — full-stack capable, AI literate, and product-accountable
• Define clear career paths, competency frameworks, and upskilling standards that prioritize hands-on engineering depth alongside functional wealth domain

knowledge
• Foster a culture of shared quality ownership — coaching developers, BAs, and product managers to participate actively in quality practices
• Partner with the engineering leadership team to define quality KPIs, sprint-level quality metrics, and release health dashboards visible to all stakeholders
• Cross-Functional Integration & Release Intelligence
• Serve as the quality owner across Digital Wealth’s cross-functional delivery squads — advisors, portfolio management, client reporting, operations, and settlements
• Partner with Release Management to automate and accelerate the Go/NoGo release process — reducing release note preparation from hours to minutes
• Integrate QA practices with SWIFT operations, reconciliation, and settlement workflows — ensuring quality extends to data accuracy and operational

correctness, not just functional behaviour
• Own the defect lifecycle — from triage and root-cause classification through resolution verification and regression prevention
• Drive environment health and readiness standards across all non-production tiers — ensuring Dev, SIT, CERT, and UAT environments are consistently stable and

observable
• Metrics, Reporting & Continuous Improvement
• Define and publish quality health metrics across the PDLC: defect escape rate,automation coverage, test execution velocity, environment stability, release risk

scores
• Use data-driven quality insights to influence product prioritization, technical debt decisions, and engineering investment
• Build a living quality knowledge base (integrated with Glean) — runbooks,regression taxonomies, test scenario libraries — that grows with every sprint and

survives team changes
• Establish AI-driven regression intelligence — predictive models that identify which areas of the product are highest risk for a given release based on change

impact analysis

Key Skills We Are Looking For

Core Engineering (Must Have)
• 10+ years of progressive QA / SDET / quality engineering experience in complex, enterprise SaaS or fintech product environments
• Hands-on expertise in test automation frameworks — Selenium, Playwright, Cypress, RestAssured, or equivalent — with a strong preference for engineers who

have built frameworks from scratch, not just maintained them
• Strong API testing expertise — REST, GraphQL, SOAP — with experience integrating API test suites into CI/CD pipelines
• Proficiency in at least one programming language — Python, Java, C#, orJavaScript/TypeScript — at a level where you can write automation code, review

PRs, and debug failures independently
• Deep experience with CI/CD integration — GitLab CI, Jenkins, or Azure DevOps —and quality gates in automated deployment pipelines
• Solid understanding of performance and load testing — JMeter, k6, Gatling, orequivalent — and experience defining NFR baselines for wealth management

platformsAI & Intelligent Quality (Strong Preference)
• Hands-on experience with AI-powered QA tooling — test generation fromrequirements, defect classification, impact analysis, or log intelligence
• Familiarity with LLM-based automation — Claude, GPT-4, or similar — forgenerating test cases, interpreting logs, and producing release documentation
• Experience with RAG-based knowledge retrieval for QA knowledge bases —runbooks, regression taxonomies, scenario libraries
• Understanding of Glean, Jira, Confluence, and GitLab integrations for AI-assisted QA workflows
• Ability to evaluate, adopt, and govern emerging AI QA tools responsibly —balancing innovation velocity with data security and compliance

Domain & Product (Preferred)
• Experience testing wealth management, financial services, or capital markets platforms — portfolio management, advisor tools, settlements, reconciliation, or

client reporting
• Familiarity with portfolio accounting systems, DataLoader patterns, or complex financial data models
• Understanding of SWIFT messaging, trade settlement, or reconciliationworkflows from a quality and data accuracy perspective
• Experience with regulatory compliance testing — ensuring products meetfinancial services governance and audit standards

Leadership & Culture (Essential)
• Demonstrated ability to lead and grow QA engineering teams — hiring, mentoring, performance management, and capability development
• Experience shifting quality left — embedding QA practices at requirements and design stages, not just execution
• Strong stakeholder communication — ability to translate quality metrics, release risk, and defect trends into clear narratives for product, engineering, and senior

leadership audiences
• Experience driving quality culture change — moving organizations from siloed testing to shared engineering quality ownership Comfortable operating in a senior individual contributor + people leader hybrid model —leading the team while remaining hands-on in architecture, tooling, and delivery

Location & Working Model

Bengaluru, India
• 3-day in-office (hybrid)
• Full-time permanent InvestCloud India
• Bengaluru
• May 2026
• Confidential — For Internal Recruitment Use ©2026 InvestCloud, Inc.
• Wealth Connected™