Senior Quality Assurance Engineer

Provenir; Bengaluru; On-site; INR 1,200,000 - 1,700,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Flexible/remote-friendly opportunities

Maternity/paternity leave

Job summary

Provenir in Bengaluru, India, is seeking a Senior QA Engineer to assure quality of our products by automating tests for microservices and front ends, and managing builds and CI/CD. You will work with graph data stores, ML models, and agentic workflows whose outputs are probabilistic and require contextual validation.

The role demands strong Python test automation, API testing, and experience with CI pipelines, plus knowledge of graph databases and containerized environments.

Qualifications

• Proven hands-on experience in automated testing of web applications and services.
• Design, develop, and execute automated tests in Python using Playwright, Selenium WebDriver, or equivalent.
• Experience testing web services and REST APIs (Postman, Swagger).
• Working knowledge of graph databases — Neo4j, Neptune, TigerGraph, JanusGraph.
• Exposure to testing AI/ML-backed features and probabilistic systems.
• CI/CD pipelines experience with Jenkins, GitHub Actions or GitLab CI.
• SQL experience and ability to work with relational data.

Responsibilities

• Design and implement end-to-end and component test suites.
• Embed quality gates in CI/CD pipelines and manage test data.
• Validate API contracts and data integrity across services.
• Build and maintain test environments using containerisation.
• Collaborate with AI/ML and data science teams on testing needs.
• Drive test reliability, track flake rates, and reduce regressions.

Skills

Automated testing architecture

Python scripting

REST API testing

Graph databases knowledge

AI/ML-backed features testing

Scripting: Unix shell/Ruby

CI/CD pipelines

SQL

Process improvement

Education

Bachelor’s Degree in Computer Science

Tools

Docker

Kubernetes

Terraform

Ansible

Jenkins

GitHub Actions

Postman

Swagger

Neo4j

GDS/Graph Analytics

Job description

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.

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 Senior QA 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 elevate issues as appropriate

What’s Required

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

Experience: Proven track record of extensive 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‑team(ing)


• 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.