QA Engineer (Manual+Automation, AI Exposure)

Total exp: 5-8 Years

Client: MRI Software

Location: Vadodara

Budget: Look for decent with experience

Mode interview: 1 Virtual

Mode of Work: Hybrid

QA Engineer:

Job Summary/Objective 

Quality Assurance Engineers at MRI collaborate closely with Product Management and Product Development teams to deliver high-quality, high-performance products for our clients. In this role, QA Engineers are responsible for creating and contributing to the documentation of user stories and acceptance criteria, working alongside product owners and development teams. They define manual and automation testing strategies, tools, scenarios, and plans for both web and mobile products, ensuring comprehensive functional and performance testing. 

 QA Engineers will execute static, dynamic, and performance testing while providing detailed reporting and feedback throughout the development lifecycle. They are expected to demonstrate strong technical skills, including expertise in back-end development, database queries, and keen attention to detail. Effective written, verbal, and organizational communication is essential. 

 In addition, QA Engineers will leverage AI to optimize and automate repetitive tasks, thereby enhancing the overall efficiency and effectiveness of QA processes, ensuring a faster, more accurate testing cycle.

Tools and technology:

1.     Tools: Jira, Xray, TFVC, Git

2.     API: REST, SOAP, SoapUI, Postman

3.     Automation: C#, JavaScript, TypeScript, Ruby, Playwright, SpecFlow

4.     Database: SQL

Total exp: 5-8 Years

Client: MRI Software

Location: Vadodara

Budget: Look for decent with experience

Mode interview: 1 Virtual

Mode of Work: Hybrid

QA Engineer:

Job Summary/Objective 

Quality Assurance Engineers at MRI collaborate closely with Product Management and Product Development teams to deliver high-quality, high-performance products for our clients. In this role, QA Engineers are responsible for creating and contributing to the documentation of user stories and acceptance criteria, working alongside product owners and development teams. They define manual and automation testing strategies, tools, scenarios, and plans for both web and mobile products, ensuring comprehensive functional and performance testing. 

 QA Engineers will execute static, dynamic, and performance testing while providing detailed reporting and feedback throughout the development lifecycle. They are expected to demonstrate strong technical skills, including expertise in back-end development, database queries, and keen attention to detail. Effective written, verbal, and organizational communication is essential. 

 In addition, QA Engineers will leverage AI to optimize and automate repetitive tasks, thereby enhancing the overall efficiency and effectiveness of QA processes, ensuring a faster, more accurate testing cycle.

Tools and technology:

1.     Tools: Jira, Xray, TFVC, Git

2.     API: REST, SOAP, SoapUI, Postman

3.     Automation: C#, JavaScript, TypeScript, Ruby, Playwright, SpecFlow

4.     Database: SQL

Required Skills:-

• 4+ years of experience in Software Testing (Manual & Automation).
• Strong experience with Selenium or Playwright.
• Hands-on experience in API Testing (Postman, REST Assured, Swagger, etc.).
• Experience with CI/CD pipelines (Jenkins, GitLab CI, Azure DevOps, GitHub Actions).
• Strong understanding of Functional, Regression, and Non-functional Testing.
• Excellent analytical and debugging skills.

AI-Specific Skills

• Hands-on experience in GenAI / AI Testing.
• Experience testing LLM-based applications.
• Strong understanding of prompt engineering and prompt validation.
• Knowledge of LLM behavior, model variability, and non-deterministic outputs.
• Experience validating AI outputs for accuracy, hallucinations, bias, and safety.
• Test data management for AI applications.
• Understanding of Responsible AI testing concepts.

About the team

SecurITe’s mission is to build an Agentic‑AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.

About the Role

We’re looking for a seasoned Senior Quality Engineer to provide technical leadership and architectural oversight for our next‑generation cybersecurity AI platform. In this high-impact role, you will define the technical strategy for quality assurance, ensuring our agentic AI transforms cyber defense with unparalleled reliability.

You will be responsible for the end-to-end quality lifecycle, from architectural reviews to the deployment of scalable automation frameworks. Beyond technical execution, you will serve as a mentor to junior team members, fostering a culture of technical excellence and driving the strategy that ensures our solutions meet the rigorous demands of critical infrastructure protection.

What You’ll Do

●    Defining and driving comprehensive QA strategies and roadmaps for the cybersecurity platform.

●    Designing, developing, and executing test plans, test cases, and automated scripts to ensure software quality.

●    Performing functional, regression, performance, scalability and security testing to identify bugs or defects.

●    Collaborating with developers, product managers, and other stakeholders to understand product requirements and testing needs.

●    Identifying, documenting, and tracking software defects, ensuring clear communication of issues and their resolutions.

●    Leading deep-dive root-cause analysis for critical system defects and security vulnerabilities.

●    Conducting thorough reviews of product specifications and software design to identify potential areas of concern before testing.

●    Architecting and designing complex, scalable test automation frameworks to optimize CI/CD velocity.

●    Ensuring the software meets customer and business requirements by validating the functionality and performance.

●    Assisting in continuously improving QA processes, tools, and best practices to enhance software testing efficiency and effectiveness.

●    Supporting user acceptance testing (UAT) and assisting clients with product validation.

●    Mentoring junior and mid-level engineers, providing technical guidance and conducting architectural reviews.

Required Experience

●    A Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.

●    8-10 years of proven experience in quality engineering, specifically within network cybersecurity, Identity Providers, or AI-integrated platforms.

●    Expertise in manual and automated testing.

●    Deep domain expertise in complex system validation and advanced automation practices at scale.

●    Proficiency in programming languages like Python to build and run automated test scripts.

●    "Strong knowledge of software testing methodologies, performance testing tools (e.g., JMeter, k6), and security traffic generation/simulation tools (e.g., Ixia BreakingPoint, Scapy, or Snort/Suricata traffic generators)."

●    Understanding of continuous integration/continuous deployment (CI/CD) pipelines and version control systems like Git.

●    Strong communication skills for documenting test results and interacting with cross-functional teams.

●    Excellent analytical skills, attention to detail, and problem-solving ability.

●    Ability to work independently as well as collaboratively in a team environment.

●    A curious mindset with a willingness to quickly learn new technologies and testing tools.

Required Skills & Qualifications

●    Familiarity with cloud-based testing environments (GCP, AWS, Azure).

●    Experience with cybersecurity products or cloud services or IDP or Web UI

The Mindset

●    Problem Solver: You thrive on complex, ambiguous challenges and engineer elegant solutions.

●    Ownership‑Driven: You take initiative, move fast, and deliver outcomes without hand‑holding.

●    Continuous Learner: You stay ahead of the curve in AI, ML, and emerging technologies.

●    Startup DNA: You excel in fast‑moving environments where priorities evolve and impact is immediate.

QA Test Engineer – Manual & Automation

Location: Bangalore, India

Experience: 2–5 years

Employment Type: Full-time

Work Mode: On-site

About Juntrax

Juntrax is a B2B Cloud SaaS product company building business operations software for SMEs. Our platform helps businesses manage their day-to-day operations through streamlined digital workflows and tools.

We are looking for a QA Test Engineer who can ensure the quality, reliability, and usability of our product through a combination of manual and automated testing.

Key Responsibilities

• Design, develop, and execute manual and automated test cases for web-based SaaS applications.
• Perform functional, regression, integration, system, and API testing.
• Create and maintain automated test scripts for critical product workflows.
• Identify, document, track, and retest bugs using appropriate bug-tracking tools.
• Collaborate closely with developers, UI/UX designers, product teams, and other stakeholders to understand requirements and ensure product quality.
• Participate in requirement analysis and contribute to test planning and test strategy.
• Perform cross-browser and responsive testing to ensure a consistent user experience.
• Validate new features, enhancements, bug fixes, and product releases.
• Maintain clear documentation of test scenarios, test cases, defects, and test results.
• Help improve QA processes, automation coverage, and overall testing efficiency.

Required Skills & Qualifications

• 2–5 years of experience in Software Quality Assurance / Testing.
• Strong understanding of manual testing concepts and QA methodologies.
• Hands-on experience with automation testing using tools/frameworks such as Selenium, Playwright, Cypress, or similar.
• Experience with API testing using tools such as Postman or similar.
• Good understanding of SQL and database validation.
• Experience with regression, integration, functional, and end-to-end testing.
• Familiarity with Git/version control and basic CI/CD concepts.
• Ability to write clear and effective test cases and defect reports.
• Good analytical and problem-solving skills.
• Strong attention to detail and a quality-focused mindset.

Good to Have

• Experience testing B2B SaaS or cloud-based applications.
• Experience with JavaScript/TypeScript, Python, Java, or another programming language.
• Experience integrating automated tests into CI/CD pipelines.
• Familiarity with Agile/Scrum development environments.
• Experience with performance or security testing.

What We’re Looking For

• Someone who can think beyond the happy path and identify edge cases and potential failure points.
• A QA professional who is comfortable working independently as well as with cross-functional teams.
• Someone who takes ownership of product quality from requirement analysis through release.
• A continuous learner who is interested in increasing automation coverage and improving QA processes.

Why Join Juntrax?

• Work directly on a growing B2B SaaS product.
• Gain exposure to the complete software development and release lifecycle.
• Opportunity to contribute to both manual and automation QA practices.
• Work closely with engineering, product, and leadership teams.
• Be part of a fast-paced startup environment where your work has a direct impact on the product.

We are currently looking for a QA Engineer (3+ years of experience) to join our team. The ideal candidate should have strong experience in Python-based testing and mobile automation for Android and iOS using Appium. In this role, you will be responsible for ensuring product quality through automated and manual testing, identifying bugs, and collaborating with cross-functional teams to deliver high-quality applications.

Key Responsibilities:

• Design, develop, and execute test cases for web and mobile applications
• Perform automation testing using Python and PyTest
• Develop and maintain mobile automation scripts for Android and iOS using Appium
• Identify, log, and track bugs, and work closely with developers for resolution
• Perform regression, functional, and integration testing
• Participate in requirement analysis and test planning
• Improve test frameworks and automation coverage
• Ensure timely delivery of high-quality releases

Required Skills:

• 3+ years of experience in QA/testing
• Strong experience in Python testing
• Hands-on experience with PyTest
• Experience in Android & iOS automation testing
• Hands-on experience with Appium
• Understanding of SDLC/STLC and Agile methodology
• Good debugging and analytical skills
• Strong communication and teamwork skills

Preferred Skills:

• Experience with CI/CD tools
• API testing knowledge
• Experience with test management and bug tracking tools

SDET – Software Development Engineer in Test

Experience: 2–5 Years

Location: Bangalore / Gurugram

Employment Type: Full-Time

Mandatory Skills

• 2–5 years of relevant experience in SDET / QA Automation / Software Testing.
• Strong hands-on experience in:
• Functional Testing
• API Testing
• Performance Testing
• Good programming/coding skills with the ability to read, write, troubleshoot, and debug code.
• Experience with automation testing frameworks/tools such as Selenium, Playwright, Cypress, Appium, etc.
• Hands-on API testing experience using tools such as Postman, REST Assured, RestSharp, or similar.
• Practical experience with performance testing tools such as JMeter, LoadRunner, k6, Gatling, or equivalent.
• Good understanding of SDLC, STLC, defect lifecycle, and testing methodologies.
• Strong analytical and problem-solving skills.

Good to Have

• Experience with Java, Python, JavaScript/TypeScript, C#, or other programming languages.
• Experience with .NET / C#.
• SQL/database testing experience.
• CI/CD tools such as Jenkins, GitHub Actions, Azure DevOps, GitLab CI, etc.
• Experience with Docker/cloud environments.
• BDD frameworks such as Cucumber or SpecFlow.
• Experience working with Agile/Scrum teams.

If Interested, share CV : snigdhaattheratebeanhr.com

Senior QA Engineer

Make quality part of the engineering system.

AbleCredit builds software for complex enterprise workflows where AI, APIs, business rules, human decisions, and real-world operations have to work together reliably. We care about building products that work in production - not just in demos. We're looking for a senior quality engineer who can move quality upstream: from release-time testing to better automation, contracts, observability, and engineering practices.

What You'll Own?

• Own quality strategy across web, mobile, backend APIs, integrations, and end-to-end workflows.

• Design and maintain automated regression suites for critical customer journeys.

• Build API, integration, contract, and workflow tests that catch failures before production.

• Partner with engineering and product teams during design - not only after development is complete.

• Define release readiness, risk-based testing, and production validation practices.

• Investigate escaped defects, identify systemic causes, and drive preventive improvements.

• Improve test data, environments, tooling, and CI integration so teams can ship confidently.

What We're Looking For?

• 5+ years in software quality engineering or test automation.

• Strong API and backend testing experience, including asynchronous and integration-heavy systems.

• Experience testing mobile and web applications and understanding client/ server failure modes.

• Ability to write automation in JavaScript/ TypeScript, Python, Java, or a similar language.

• Strong debugging skills across logs, network requests, databases, and distributed services.

• Experience with CI/CD and integrating automated tests into release pipelines.

• A product mindset: prioritize risk and customer impact rather than maximizing test-case counts.

Nice to Have

• Performance, load, security, or reliability testing.

• Experience with Playwright, Cypress, Appium, Postman/ Newman, k6, or similar tooling.

• Experience with event-driven systems, queues, webhooks, and long running workflows.

• Experience testing AI-assisted or non-deterministic product behavior.

How We Think About Quality?

Quality is an engineering responsibility. Automation should create confidence, not dashboards. A production escape should improve the system that allowed it to happen. The goal is simple: ship quickly without making customers our test environment.

What you'll own

The quality charter. Define and evolve the testing strategy — web application, dashboards, APIs, webhooks, and customer integrations. Establish release criteria, coverage expectations, and quality gates that engineers actually respect because they're fast and they catch real bugs. Automation at scale. Build and maintain end-to-end and API automation suites that run on every PR and give a trustworthy signal. Own the flake rate. Design for parallel execution, deterministic test data, and fast feedback — a suite nobody trusts is worse than no suite. Performance and reliability. Design and run load, stress, and soak tests against APIs and the platform. Profile results, isolate bottlenecks with the engineers who own the service, and set up the monitoring that tells us about degradation before a customer does. Leverage through tooling, including AI. Use whatever gets coverage up and cycle time down: LLM-assisted test case generation from specs, AI-assisted authoring and maintenance of automation, synthetic test data generation, log and failure triage. We expect you to be opinionated about where these tools genuinely help and where they produce impressive-looking noise. Raising the bar. Partner with product and engineering from spec through release so quality risk is surfaced during design, not after code freeze. Mentor the QA team and build the practices — bug triage discipline, root cause analysis, prevention over detection — that outlast any single release.

What we're looking for

Must have

3–6 years in QA roles, with meaningful ownership of automation frameworks rather than only executing existing suites.

Strong test automation skills with a modern framework — Playwright, Cypress, or Selenium — and solid coding ability in Python, JavaScript/TypeScript, or Java. You should be comfortable reading application code, not just testing around it.

API testing experience: REST, auth, webhooks and asynchronous event flows, contract testing, and tooling such as Postman, REST Assured, or Pact.

Hands-on CI/CD integration — GitHub Actions, GitLab CI, Jenkins, or equivalent — including making suites fast and reliable enough to gate merges.

Working knowledge of SQL for validating data correctness, and comfort with logs, traces, and observability tooling for debugging.

Rigorous, systematic thinking about edge cases and failure modes, and the communication skills to make quality risk legible to product and leadership.

Nice to have

Experience testing AI, ML, or LLM-based products, and comfort with the reality that outputs are probabilistic rather than deterministic. Familiarity with Docker, Kubernetes, or cloud infrastructure for standing up test environments.

Performance and load testing with k6, JMeter, Gatling, or Locust, plus the analytical ability to turn results into a specific, actionable bottleneck. Exposure to enterprise SaaS with real integration surface area, or to security and compliance testing expectations of enterprise buyers. - Experience as the first or most senior quality voice on a team.

What we offer

Competitive compensation with equity. Direct ownership of a charter that materially affects how enterprise customers experience our product.

Proximity to frontier AI systems in production, and the freedom to use modern tooling to do your job well.

A fast-moving team where the distance between an idea and a shipped change is short.

Principal Software Engineer

Location: Bangalore India

Department: AI Engineering / Quality Assurance

Experience Level: Mid to Senior

We are looking for a highly motivated Senior AI Test / Automation Engineer to design and scale automated validation frameworks for AI/ML models, LLM-based applications, and agentic systems. This role is critical to ensure that AI solutions meet enterprise standards for quality, reliability, safety, and compliance before and after production deployment.

Key Responsibilities

• Build and maintain AI test automation frameworks for pre-qualification and continuous validation of models and agent workflows
• Develop comprehensive test suites, including:
• Unit, integration, and end-to-end (E2E)
• Functional, regression, performance, and safety testing
• Validate AI system behavior, including:
• Non-deterministic LLM outputs
• Hallucinations and edge cases
• Multi-step agent decision-making
• Design and manage evaluation systems:
• Golden datasets
• Benchmarking pipelines (accuracy, latency, reliability)
• Automate testing within CI/CD pipelines for model updates, prompt changes, and tool integrations
• Implement observability and telemetry to enable traceability, monitoring, and audit readiness
• Collaborate cross-functionally with ML, MLOps, Product, and Security teams to define quality gates and release criteria
• Track and report quality KPIs, including test coverage, defect leakage, and system reliability
• Drive root-cause analysis and continuous improvement across the AI testing lifecycle

Required Skills

Core Engineering

• Strong programming skills in Python; familiarity with Bash, TypeScript, or Go
• Experience with test automation frameworks such as PyTest, Playwright, Selenium, or Cypress
• Proficiency in CI/CD tools (GitHub Actions, Jenkins, GitLab CI)
• Experience with cloud platforms (AWS, Azure, GCP) and containers (Docker, Kubernetes)

AI / ML & Agentic Systems

• Hands-on experience with LLM ecosystems (OpenAI, Anthropic, Bedrock)
• Familiarity with:
• RAG architectures and vector databases (Pinecone, Weaviate)
• Agent frameworks (LangChain, LlamaIndex, AutoGen)

AI Testing Techniques

• Experience with non-deterministic testing approaches (statistical assertions, tolerance thresholds)
• Knowledge of evaluation methods:
• LLM-as-a-judge
• BLEU, ROUGE, semantic similarity scoring
• Experience with prompt and agent regression testing
• Understanding of AI safety testing, including adversarial testing, bias/fairness validation, and jailbreak detection

Tooling (Preferred)

• AI testing & observability tools: LangSmith, TruLens, Arize, Weights & Biases
• Evaluation tools: DeepEval, Ragas, PromptFoo, Giskard
• Monitoring: Prometheus, Grafana, OpenTelemetry

Soft Skills

• Strong analytical and problem-solving skills
• Excellent communication and cross-functional collaboration
• Data-driven mindset with focus on quality KPIs
• Detail-oriented with a strong bias toward automation and scalability

Experience Requirements

• 7+ years in QA, SDET, or test automation engineering
• Proven experience building and scaling automation frameworks
• Hands-on experience with AI/ML systems or LLM-based applications
• Experience testing RAG pipelines or agentic workflows
• Owned end-to-end AI test strategy and architecture
• Defined quality metrics and release gates
• Delivered scalable validation pipelines for production AI systems
• Supported audit and compliance readiness

Preferred

• Experience in enterprise or regulated environments (SOC2, ISO 27001, etc.)
• Exposure to:
• Shift-left testing practices
• Production observability and monitoring
• Chaos or resilience testing

Senior-Level Differentiators

Education

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field

Nice-to-have:

• ISTQB certification
• Cloud/ML certifications (AWS, Azure, GCP)
• AI testing certifications

What Success Looks Like

• AI systems that are accurate, reliable, and safe
• Fully automated test pipelines integrated into CI/CD
• Measurable improvements in defect leakage and model quality
• Strong observability and auditability across AI systems
• Scalable validation frameworks supporting rapid AI innovation