Agentic Platform QA Engineer

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

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.

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

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.

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

We are seeking a forward-thinking Mid-Level QA Automation Engineer specializing in RPA, financial systems validation, and AI engineering. You will build and scale end-to-end automation workflows using UiPath for our financial services platform. Additionally, you will pioneer our testing evolution by leveraging prompt engineering, creating custom AI agents, and implementing Model Context Protocol (MCP) servers to bridge AI models with our testing infrastructure.

Key Responsibilities and Duties

   RPA Automation:

·    Design, develop, and maintain robust automated testing workflows using UiPath Studio.

 AI Agent Engineering:

·   Architect, build, and orchestrate custom AI agents to autonomously generate,execute, and self-heal test scripts.

Prompt Engineering:

·   Design, optimize, and manage advanced prompt templates to drive deterministic,high-quality code and test case generation from LLMs.

 MCP Integration:

·    Implement and configure Model Context Protocol (MCP) ecosystems to securely connect AI agents with local data, development tools, and testing environments. 

 Financial System Testing:

·   Validate end-to-end trade life cycles, market data processing, and capital market clearing workflows. 

Regression Orchestration

·   Manage continuous regression schedules via UiPath Orchestrator to ensure financial system stability. 

Mandatory skills

Project Mandatory Skills

Project Desired Skills

UiPath Studio and Orchestrator (UI/API automation activities)

Selenium or Playwright for web-based application testing

Building, deploying, and scripting autonomous AI agents for complex engineering workflows

Calypso treasury and capital markets platform

Prompt engineering — context injection, few-shot prompting, and guiding LLMs to exact test requirements

FitNesse for acceptance testing and collaborative documentation

Model Context Protocol (MCP) — using or developing MCP servers/clients to connect AI tools to external data sources and developer environments

TypeScript, Python, or Java to support agent tool calling and framework extensions

 Qualifications

• 3+ years of professional software QA automation or RPA development experience.
•  Strong understanding of capital markets, trading lifecycles, treasury workflows, or core banking architectures.
• Strong communication and collaboration skills to work across engineering, QA, and business teams.

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.

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.

Job Opportunity: QA Automation Engineer at FrontM

Location: Bangalore preferred / Hybrid as applicable

Experience: 5–6 years in Quality Assurance roles

Education: B.E/B.Tech in Computer Science, Engineering or a related technical discipline

Salary: Above market standards, flexible for the right candidate

Career growth: Long-term opportunity with potential to lead test automation strategy and quality engineering

About FrontM

FrontM builds software platforms for frontline workforces operating in remote and low-connectivity environments, with a strong focus on the maritime industry. The platform supports communication, collaboration, healthcare, learning, welfare and operational workflows across mobile, web, kiosk and connected device environments.

The platform is used across web, iOS, Android and integrated services in demanding real-world conditions, requiring disciplined test strategy, reliable automation and close attention to quality at every release.

Role Summary

As a QA Automation Engineer, you will bridge the gap between manual testing and automated solutions to ensure the delivery of high-quality software. You will design, develop and execute automated test scripts for FrontM’s web, mobile and API interfaces, working closely with developers and product managers so that quality is built in from the start.

This role requires strong hands-on experience with modern testing frameworks including Playwright, Appium and Cucumber, and comfort using AI tools to accelerate test case generation and script creation.

Key Responsibilities

Test Strategy & Automation Frameworks (≈40%)

• Review product requirements and technical design documents to create comprehensive, well-structured test plans and test cases covering both manual and automated strategies
• Design, build and maintain scalable automated test frameworks for web applications using Playwright
• Design, build and maintain automated tests for mobile applications on iOS and Android using Appium
• Write clear, business-readable test scenarios and implement BDD frameworks using Cucumber
• Use modern AI tools such as ChatGPT, GitHub Copilot or specialised QA AI tools to generate test cases, write boilerplate automation scripts and identify edge cases

API, Integration & CI/CD Testing (≈40%)

• Perform robust API integration testing to ensure seamless communication between microservices and external endpoints
• Integrate automated tests into the CI/CD pipeline to ensure continuous quality and rapid feedback for the development team
• Maintain and extend regression suites so they remain reliable as the platform evolves

Defect Management & Collaboration (≈20%)

• Identify, record, document and track bugs thoroughly through to resolution
• Perform thorough regression testing when bugs are resolved
• Work closely with cross-functional teams, including developers and product managers, to identify system requirements and ensure quality is built in from the start

Required Technical Skills

Test Automation & Frameworks

• Proven work experience in software quality assurance, with a strong foundation in manual testing methodologies and a transition into automation
• Strong hands-on experience writing automated tests using Playwright for web and Appium for mobile
• Solid experience implementing and maintaining Cucumber for Behaviour-Driven Development

API, Programming & CI/CD

• Deep understanding of RESTful APIs and hands-on API integration testing experience using tools such as Postman, RestAssured or Playwright API testing
• Proficiency in at least one relevant programming language such as JavaScript, TypeScript, Java or Python, with TypeScript/JavaScript highly preferred for Playwright
• Experience with Git and CI/CD tools such as Jenkins, GitHub Actions or GitLab CI

AI-Assisted Testing & Quality Practices

• Demonstrated ability to prompt and use AI coding assistants and generative AI tools to build test scripts, generate test data and brainstorm test scenarios
• Understanding of Agile/Scrum development principles
• Experience with performance and security testing

Personal Attributes

• Strong ownership mindset for product quality and release readiness
• Methodical, detail-oriented approach to testing, documentation and defect tracking
• Clear written and spoken communication in English
• Ability to work independently and collaborate effectively with developers and product managers
• Comfortable working in fast-moving engineering teams
• Curiosity and willingness to adopt new tools, including AI, to improve QA efficiency

Why join FrontM?

Long-Term Career Growth

Opportunity to shape quality engineering for software used by global maritime and remote workforce customers, with scope to grow into test automation leadership roles.

Engineering Challenges That Matter

Test applications used in remote, low-bandwidth and operationally demanding environments, where reliability matters.

Broad Technical Ownership

Take responsibility across web, mobile and API testing, BDD, CI/CD integration and AI-assisted quality practices.

Apply now

Join a team focused on building reliable software for real-world use cases and help ensure the quality of systems used across the global maritime workforce.

• 12 - 16 years of experience in Enterprise Software Product Engineering (Development/Quality) 
• Working experience with Enterprise SaaS product companies 
• 6+ years of experience in leading/managing multi-discipline activities - manual, automation, performance and security testing. 
• Experience with AI powered test automation frameworks like Playwright, TestRigor etc is preferable. 
• Experience with security and performance testing tools like BurpSuite, Locust, K6 etc   
• Strong experience in generating and presenting data/metric driven reports to exec/C-level stakeholders. 
• Self drive to achieve team and organization goals with high ROI 
• Result oriented collaborator and enabler of success. 
• Preferred: 
• Enterprise software experience withing the Life Sciences industry and good understanding of GxP requirements 
• Knowledge of cloud native, distributed architecture 

Responsibilities:

• Lead the overall strategy, execution, reporting of ValGenesis’s platform/integration testing activities 
• Own the strategic vision and establish the Software QA processes, tools, frameworks. Ensure, Monitor and Measure of the same in terms of rollout, adoption, results. 
• Change advocate of lean and efficient working – Processes, Tools, Resources. 
• Work with the engineering and cross-functional leaders along with the developers/testers to achieve continuous and incremental quality improvement across all products. 
• Own and deliver automation, security, performance testing frameworks/tools/strategies.  
• Enable the adoption of such tools/frameworks during development phase. 
• Build tools to monitor and generate metrics of all QA activities - test definition, execution, results, production incidents etc. 
• Build a strategy and deliver capabilities to fully automate computer software validation for all product releases. 
• Build and sustain high performance teams – Hiring, Performance and Talent Management