Principal Software Engineer at Cadence Design Systems · Bengaluru (Bangalore) · 2 - 10 years · ₹15L - ₹35L / yr · Profitable · Posted 13 Oct 2026
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 Cadence Design Systems
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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.
Strong Senior QA/SDET Profile with hands-on automation building and QA-function ownership
2
Mandatory (Experience 1): Must have 6+ years in QA/test automation/SDET roles with clear progression in scope (Engineer to Senior to Lead)in a B2B SaaS product company
3
Mandatory (Experience 2): Must have direct experience scaling a QA function at a SaaS company and building automation frameworks or QA processes from scratch
4
Mandatory (Tech skill 1): Must have hands-on UI automation experience with Selenium (Java + TestNG) or Playwright / Cypress (JavaScript / TypeScript) using maintainable design patterns like Page Object Model
5
Mandatory (Tech skill 2): Must have API testing & automation experience with Postman and RestAssured (or equivalent) for functional, integration, and contract testing
6
Mandatory (Tech skill 3): Must have experience with CI/CD integration (Jenkins or GitHub Actions) and Git for version control
7
Mandatory (Skill 1): Must have a strong grasp of Agile / Scrum delivery and JIRA for defect and test management
8
Mandatory (Skill 2): Must have experience leading or mentoring QA engineers and collaborating cross-functionally with developers and product teams
9
Mandatory (Skill 3): Must have solid experience using AI in test automation and manual testing exposure
10
Mandatory (Communication): Must have strong communication skills for cross-functional collaboration
11
Mandatory (Company): Must come from a B2B SaaS
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.
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.
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.
About the role
We need a senior QA professional to assess our current QA practices, set up the right processes, and guide junior team members on execution. You will then scale the practice with Playwright automation.
Responsibilities
Assess existing QA processes, tools and coverage; identify gaps and drive an improvement roadmap.
Define test strategy, QA processes and quality metrics (coverage, defect leakage, release sign-off).
Guide and mentor junior QA engineers on test design, execution and automation.
Build a scalable Playwright (TypeScript) framework for UI and API tests.
Integrate automation into CI/CD with quality gates and clear reporting.
Drive adoption of AI in testing: agentic AI for test generation, self-healing scripts and failure triage, using Playwright MCP and similar tools.
Define QA approaches for AI-powered features, including LLM output evaluation and agent workflow testing.
Partner with dev and product teams to make quality a shared responsibility.
Must have
8–10 years in QA, 4+ years in test automation.
2+ years hands-on Playwright with TypeScript/JavaScript.
Proven experience assessing and setting up a QA practice from scratch.
Strong API testing, CI/CD (GitHub Actions, Jenkins or similar) and Git skills.
Experience leading and coaching junior QA engineers.
Hands-on use of AI coding assistants and agentic AI tools (e.g. Playwright MCP, Claude, GitHub Copilot) in QA workflows.
Good to have
Selenium/Cypress to Playwright migration experience.
Performance, accessibility or visual testing exposure.
ISTQB or equivalent certification.
Experience building or testing MCP servers, AI agents or LLM-based applications (evals, prompt and guardrail testing).
Role Overview
We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale.
Key Responsibilities
Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production.
Write clean, tested, production-grade code and participate actively in code and design reviews.
Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production.
Required Qualifications
8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs.
Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel).
Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers.
Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability.
Job Title: Java SDET / Automation Test
Experience: 5+ Years
Location: Hyderabad
Work Mode: 4 Days WFO
Interview Process:
- L1: Case Study – GitHub Repository
- L2: Face-to-Face – Hyderabad
Job Summary
We are looking for an experienced Java SDET / Automation Test Lead with strong expertise in Java, Selenium, automation testing, and AI-powered testing tools. The candidate will be responsible for leading automation testing activities, developing robust test frameworks, ensuring product quality, and improving testing efficiency using AI tools.
Mandatory Skills
- Java
- Selenium WebDriver
- Automation Testing / SDET
- Test Automation Frameworks
- Test Planning & Test Case Development
- AI Tools for Development & Test Automation
- End-to-End Testing
- Test Data Creation
- Defect Tracking
Preferred Skills
- AI Testing Frameworks
- API Testing – Postman / SoapUI
- Performance Testing
- CI/CD
- Agile/Scrum
- Database Testing & SQL
Roles & Responsibilities
- Lead software testing activities and ensure high-quality deliverables.
- Design, develop, and execute automated test scripts using Java and Selenium.
- Develop and maintain test plans, test cases, and test data.
- Identify, document, and track defects.
- Mentor and guide junior testers.
- Collaborate with development teams to improve testability and automation strategies.
- Use AI tools to improve testing and automation efficiency.
- Participate in code reviews and contribute to testing best practices.
- Perform end-to-end testing and ensure application quality.
- Report testing progress and results to stakeholders.
📩 Interested candidates can share their updated resumes:
Email: pavithra.e @vysystems. com
Contact: 8 9 2 5 8 0 2 4 5 7
Job Title – Staff QA Automation Engineer
Location - India, Remote
EGNYTE YOUR CAREER. SPARK YOUR PASSION.
Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 22,000+ customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you’re not just landing a new career, you become part of a team of Egnyters who doers, thinkers, and collaborators are who embrace and live by our values:
- Invested Relationships
- Fiscal Prudence
- Candid Conversations
ABOUT EGNYTE
Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 22,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere. For more information, visit www.egnyte.com.
Egnyte is looking for an experienced Staff QA Automation Engineer to join our team and work on some exciting projects. You should possess excellent communication skills in addition to the desired technical experience.
WHAT YOU’LL DO:
What You’ll Do (but is not limited to):
- Create automated processes to build Egnyte software packages which will be deployed in production environments
- Develop automatic tools to provision build/test environments on cloud infrastructure for hosting internal development and QA activities
- Prepare deployment solutions for QA, staging and production environments
- Create and maintain tools responsible for delivering on-premise services to customer (for example, on-premises server restart and software update)
- Contribute to the development processes, including enhancements to build procedures, test frameworks, verification tools and packaging
- Provide tools and automation workflows to increase software developer productivity
- Assist in defining the process models and tool sets to enable adoption of DevOps methodologies.
Your Qualifications:
- Experience with the Linux operating system, including configuration of subsystems such as storage, networking and file systems
- Strong knowledge of CI/CD tools such Jenkins, git, puppet, ansible, terraform and hands-on experience in implementing automated branching, build, test-automation and deployment pipelines
- Demonstrated abilities of writing and troubleshooting system level scripts in python and bash
- Familiarity with Linux packaging tools such as apt and automated package update mechanisms
- Familiarity with Windows OS internals and experience with QA automation on windows..
- Ability to work with multi-cultural, globally distributed teams to a common unifying product vision and closely coordinate with cross-functional teams in different time-zones.
- Passion to deliver enterprise-grade products to customers and to continuously work with engineering team to refine the product in the field.
- Experience on using AI tools to develop skills, hooks and scheduler
Education and experience:
- Bachelor’s degree in computer science, Computer Engineering or equivalent.
- Minimum 8 years industry experience as a software developer or quality engineer with enterprise software testing.
BENEFITS
- Competitive salaries
- Medical insurance and healthcare benefits for you and your family
- Fully paid premiums for life insurance
- Flexible hours and PTO
- Mental wellness platform subscription
- Gym reimbursement
- Childcare reimbursement
- Group term life insurance
COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION:
At Egnyte, we celebrate our differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be.
Any employees with questions or concerns about equal employment opportunities in the workplace are encouraged to bring these issues to the attention of hrategnyte.com. Egnyte will not allow any form of retaliation against employees who raise issues of equal employment opportunity. If employees feel they have been subjected to any such retaliation, they should contact hrategnyte.com. To ensure the workplace is free of artificial barriers, violation of this policy including any improper retaliatory conduct will lead to discipline, up to and including discharge. All employees must cooperate with all investigations conducted pursuant to this policy.
Senior QA Analyst (Agentic AI)
Location - Chennai
Experience - 5-8 yrs
Job Summary -
Defines, develops, maintains, and executes test scripts for IT projects and/or maintenance items in
an Agile environment utilizing Atlassian JIRA and Zephyr for sprint backlog and test management.
Strives to ensure that user stories and/or system requirements are satisfied for internal and external application users. Ensures project/sprint testing is complete, and testing risks are identified before
implementation. Manages defects from identification to closure through the Software Development Life Cycle. Leverages agentic AI tools and AI-assisted testing platforms to accelerate test design, script
generation, and defect triage, while applying sound professional judgment to validate AI-generated outputs and safeguard overall test quality.
Job Responsibilities -
• Integrated Scrum team member responsible for upholding and ensuring quality assurance standards; contributes and participates in all Scrum activities and ceremonies.
• Defines, develops, and maintains test scripts, leveraging agentic AI tools (e.g., AI-based test-generation and self-healing automation agents) to accelerate script creation and upkeep. Reviews test scripts—including those authored or modified by AI agents—and provides
feedback to less experienced team members.
• Independently executes test plans and test scripts based on planned project schedules and in accordance with QA methodology.
• Proactively escalates issues to the Product Owner/Tech Lead and alerts the project/Scrum team on potential impact to the test schedule.
• Records and tracks defects uncovered during the execution of test scripts, including those surfaced by autonomous AI testing agents. Drives defects toward resolution; proposes and designs retest cases, scripts, and data, using agentic AI to accelerate root-cause analysis where appropriate. Contributes to defect management: defect status, root cause, and daily triage meetings.
• Provides timely and accurate defect status information and appropriate metrics to facilitate QA reporting. Reports individual status: dashboard information, open issues, and risk analysis.
• Participates in validation of release candidate/production deployments and production support testing as needed.
• Provides consistent and uninterrupted testing services to the organization and minimizes risk of system downtime.
• Reviews requirements/user stories and specifications and provides input during requirements and specification walkthroughs.
• Develops and executes SQL queries.
• Configures, directs, and supervises agentic AI testing tools within the QA workflow, including AI agents that generate, execute, and self-heal test scripts. Validates agent-produced results for accuracy and completeness and escalates cases where AI output requires deeper human judgment or intervention.
• Applies effective prompt engineering and critically reviews AI-generated test artifacts (test cases, scripts, data, and defect summaries) for correctness, coverage, and compliance with QA
standards, serving as the human-in-the-loop checkpoint for AI-driven testing activities.
• Uses Claude Code to author, execute, and validate Playwright automation test scripts for UI and API test coverage, reviewing and refining AI-generated automation code to ensure it meets QA
coding standards and reliably validates application behavior.
• Contributes to the development of test plans, the project testing approach, and related documents. Understands and contributes to the process of test estimates and project schedules.
• Participates in test planning, test case design, and test script walkthroughs with QA Leads. Understands testing to be accomplished and suggests changes for efficiencies within or between
projects. Actively participates and contributes to the QA design.
• Adheres to established standards and methodologies, including responsible use and governance of agentic AI testing tools. Utilizes tools and methodologies, including agentic AI and automation platforms, to improve individual effectiveness and increase efficiencies in the QA
process.
• Develops and sustains appropriate relationships and communication with peers and other project team members.
Requirements -
• Bachelor's degree or an equivalent combination of education and work experience.
• Minimum of 5–8 years' experience in Quality Assurance.
• 1+ years' experience leading test projects. Training in project management or equivalent knowledge.
• Experience with, or strong aptitude for, agentic AI and AI-assisted testing tools (e.g., AI-based test generation, self-healing automation, autonomous QA agents) is highly desirable.
Skills -
• Strong leadership capabilities, good judgment, and the ability to work effectively with a diverse workforce.
• Excellent verbal and written communication skills.
• Strong analytical, problem-solving, and planning ability. Detail-oriented and Observant.
• Ability to multitask to accomplish workload efficiently. Excellent time management.
• Good work ethic and general business acumen.
• Proficient in the Microsoft Office suite.
• Working knowledge of agentic AI and AI-assisted testing tools; ability to apply prompt engineering, critically evaluate AI-generated test artifacts, and maintain human oversight and accountability over AI-driven testing outputs.
• Hands-on experience with the Playwright test automation framework and with Claude Code or similar agentic coding tools for generating, executing, and validating automation scripts.
• Experience with the system development lifecycle. Extensive knowledge of test engineering methodologies.
• Working knowledge of testing concepts, verification and validation techniques, defect management, quantitative methods, risk management, and measurement programs.
• Understanding of relational database principles, client/server infrastructure, and n-tier architecture concepts.
• Working knowledge of defect tracking, quality principles, and testing tools.
• Knowledge of MS SQL Server, AWS Postgres, Web, Mobile, Accessibility, and Middle tier testing.
Professional Competencies -
• Ethical decision making: acts in the best interest of the organization, demonstrates integrity in all situations, and holds self and others to the organization's values.
• Focus on business results: understands the financial implications of business decisions, sets ambitious goals, and prioritizes sustained business performance.
• Honoring commitments: meets or exceeds performance expectations and inspires trust by delivering on promises.
• Embracing change: participates actively in the change process, shows resiliency and commitment during times of change, revises priorities and adapts project plans or work tasks as
needed, and takes initiative to improve own capabilities as the business changes.
• Service delivery: delivers service in compliance with contracted agreements, meets or exceeds established performance standards, and uses available tools and systems to deliver timely, accurate work.














