Quality Assurance Engineer

Reposted One Month Ago
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Hiring Remotely in Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office or Remote
Senior level
Artificial Intelligence • Fintech • Machine Learning • Software
The Role
Design and automate performance tests for microservices, APIs, UIs, and databases. Execute load, scalability, and stress tests, monitor and analyze metrics, identify bottlenecks, recommend fixes, and integrate tests into CI/CD pipelines while collaborating with dev teams.
Summary Generated by Built In

Who We Are

Provenir is the unified Decision Intelligence Platform that gives enterprises full control over end- to-end customer decisioning — to manage risk, drive growth, and transform business outcomes. By consolidating data, AI models, intelligence, agents and governance into a single decisioning environment, Provenir empowers business teams to configure and evolve strategy directly, while maintaining enterprise-grade reliability and regulatory compliance. Trusted by 120+ institutions in 60+ countries, Provenir processes over 4 billion decisions annually — turning architectural coherence into sustained risk performance and measurable value. Ready to solve meaningful challenges, work with enterprise customers, and help shape the future of AI-powered decisioning? Join us.

The QA Automation Engineer will be responsible for assuring the quality of our products, creating automated tests, and managing builds and continuous integration. You will automate tests for microservices and their related front ends, and manage infrastructure across development and production cloud environments.

This role goes beyond conventional application testing. Our platform combines graph data stores, graph analytics, machine learning models, and agentic AI workflows — systems whose outputs are probabilistic, whose correctness is contextual, and whose decisions carry regulatory weight. You will help define what “passing” means for components that don’t return the same answer twice, and build the harnesses that hold them to it.

 

What You’ll Do

 

Core Test Automation

  • Build and maintain end-to-end and component test suites using modern browser automation with auto-waiting, trace-based debugging, and parallel execution as the default

  • Shape coverage around the test pyramid rather than the UI — API and contract tests as the primary safety net, with UI reserved for genuine user journeys

  • Embed quality gates directly in CI/CD pipelines — sharded parallel runs, risk-based test selection, and pass/fail criteria that block promotion without manual sign-off

  • Provision ephemeral, containerised test environments on demand through infrastructure-as-code, with synthetic and masked test data generated per run instead of maintained by hand

  • Treat test reliability as a product: track flake rates, quarantine and fix unstable tests, and hold suites to explicit stability and runtime SLAs

  • Use AI-assisted tooling for test authoring, coverage gap analysis, and locator resilience — while owning the judgement call on what the generated tests are actually worth

  • Work shift-left alongside engineers — contributing test coverage with the feature, not after it — and partner on triage to drive issues to root cause

 

Graph Data and Analytics

  • Design and automate validation for graph database layers — schema integrity, relationship correctness, and query behaviour across Cypher, Gremlin, or SPARQL

  • Build regression coverage for graph analytics outputs: pathfinding, centrality, community detection, and link analysis used in fraud-ring identification and network risk scoring

  • Validate graph ingestion and transformation pipelines for data completeness, deduplication, and referential accuracy at scale

 

AI/ML and Agentic Systems

  • Develop evaluation harnesses for ML model behaviour — accuracy thresholds, drift detection, bias and fairness checks, and explainability outputs required for regulatory review

  • Build automated test suites for agentic workflows: tool-calling correctness, multi-step orchestration, context handling, failure recovery, and guardrail enforcement

  • Design assertion strategies for non-deterministic outputs, including golden-set comparison, semantic similarity scoring, and LLM-as-judge evaluation

  • Establish prompt and model regression testing so behavioural changes are caught before release

  • Validate feature pipelines and training/serving consistency in partnership with data science teams

 

Process and Platform

  • Incorporate best practices into dev/test/deploy processes and recommend improvements

  • Support application onboarding to the defined target operating model to achieve build and release automation

  • Document, track, and escalate issues as appropriate

 

What’s Required

Education: A Bachelor’s Degree in Computer Science or a related field.

 

Experience:

Proven track record of hands-on experience in automated testing of web applications and services, including designing, developing, and executing automated tests in Python using a modern browser automation framework (Playwright, Selenium WebDriver, or equivalent).

Qualifications, Strengths and Skills

  • Demonstrated understanding of maintainable test architecture — Page Object Model or equivalent patterns — for end-to-end testing

  • Extensive hands-on experience on Python scripting

  • Experience testing web services and REST APIs (Postman, Swagger)

  • Working knowledge of graph databases — Neo4j, Amazon Neptune, TigerGraph, JanusGraph or similar — including writing and validating graph queries

  • Exposure to testing AI/ML-backed features, and a clear grasp of why probabilistic systems need different assertions than deterministic ones

  • Scripting experience beyond Python: Unix shell, Ruby, or similar

  • Continuous integration and pipeline-based delivery (Jenkins, GitHub Actions, GitLab CI, or similar)

  • Experience with SQL

  • Experience recommending process improvements

 

Nice to Have

  • Hands-on experience with agentic frameworks — LangChain, LangGraph, Model Context Protocol (MCP), or comparable orchestration tooling

  • Familiarity with LLM evaluation tooling and practices: golden datasets, rubric-based scoring, hallucination and jailbreak testing, red-teaming

  • Graph analytics libraries such as Neo4j GDS, Apache Spark GraphX, or NetworkX

  • Observability-driven testing — synthetic monitoring, canary analysis, and validation through traces, logs and metrics

  • Docker, Kubernetes, Terraform, Ansible; microservices, container deployment and service orchestration

  • Cloud APIs (AWS, Azure, GCP)

  • JIRA for issue tracking and escalation

 

Our employees are our top priority; we offer comprehensive health and wellness plans. You will enjoy paid time off and company holidays, flexible and remote-friendly opportunities, and maternity/paternity leave.

At Provenir, we recognize that diversity and inclusion make our teams stronger. We are committed to equal employment opportunity and welcome everyone regardless of race, colour, ancestry, religion, national origin, age, sex, gender identity, sexual orientation, disability, marital status, domestic partner status, citizenship, or veteran status or medical condition. We encourage people from all backgrounds to apply.

Skills Required

  • Bachelor's Degree in Computer Science or related field
  • 7+ years of experience in Performance Engineering/Testing and/or Tools Development
  • Advanced knowledge of performance testing concepts (load, endurance, stress, failover)
  • Proven background in non-functional requirements testing from strategy to execution
  • Experience designing and executing performance testing for API, Web, and databases
  • Strong understanding of SDLC and performance testing methodologies
  • Experience identifying and troubleshooting root causes of performance issues across application, system, middleware, and database
  • Experience providing recommendations to resolve performance bottlenecks
  • Experience with test and server monitoring tools (AppDynamics, Jenkins, Splunk etc.)
  • Benchmarking, database performance analysis, capacity sizing and optimization
  • Database performance engineering for MySQL/PostgreSQL (tuning, scaling, query analysis)
  • Java and JavaScript experience including JVM tuning, GC, heap and thread dump analysis
  • OS performance monitoring, troubleshooting and configuration (Unix/Linux)
  • System design and architecture knowledge
  • Advanced JMeter (or other industry standard load testing tools) scripting
  • Experience with API and UI performance test tools
  • Proficiency with cloud deployments (AWS, Azure, GCP)
  • Build and release management experience
  • Experience with agile software development methodologies (Scrum)
  • Experience with concurrency, multithreading, and distributed system architectures
  • Understanding of database schemas, indexing, and performance optimization techniques
  • Experience with Docker, Kubernetes, microservices and container orchestration
  • Experience using and/or developing on Unix/Linux platform
  • Experience adopting AI tools to accelerate performance engineering and ability to validate AI outputs
  • Experience performance testing AI/ML-driven and decisioning systems
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The Company
HQ: Parsippany, NJ
286 Employees
Year Founded: 2004

What We Do

Provenir is a global leader in AI-powered risk decisioning and data analytics software. The company provides a low-code, cloud-native platform that helps financial institutions, including banks, fintechs, and lenders, automate the entire customer lifecycle—from credit risk onboarding and identity verification to customer management and collections. Their mission is to empower businesses to make smarter, real-time decisions to drive growth and improve customer experiences.

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