ai qa engineer

Siemens

<div>
 Siemens Digital Industries Software is a global leader in Electronic Design Automation (EDA) software, hardware, and design solutions. We partner with the world&rsquo;s leading producers of semiconductor microelectronic circuits and systems, enabling them to design and produce cutting-edge electronic products faster and more efficiently.
 
 
 We&rsquo;re excited to share that the
 
 Siemens EDA Central AI QA team
 
 is growing! This team develops core AI technologies that power the entire Siemens EDA product portfolio.
 
 
 We are hiring
 
 4 talented AI QA Engineers
 
 to join our EDA AI QA team in
 
 Cairo, Egypt
 
 . In this role, you&rsquo;ll be at the forefront of testing cutting-edge AI solutions for electronic design automation applications &mdash; including GenAI chatbots and more. You&rsquo;ll also collaborate closely with cross-functional teams across Siemens to help integrate these AI capabilities into EDA products.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Design, develop, and execute comprehensive test plans and cases to validate AI application functionality.
 </li>
 <li>
 Create innovative test scenarios that reflect real customer use cases, identifying issues and recommending improvements.
 </li>
 <li>
 Perform both manual and automated testing of conversational flows, APIs, integrations, and overall system performance.
 </li>
 <li>
 Identify, analyze, troubleshoot, and clearly report issues.
 </li>
 <li>
 Stay current with industry trends and best practices in AI and conversational platform testing.
 
 
 </li>
 </ul>
 Qualifications:
 
 
 <ul>
 <li>
 B.Sc./M.Sc. in Software or Electronics Engineering with 0&ndash;3 years of experience.
 </li>
 <li>
 Good understanding of AI, ML, and LLM basics.
 </li>
 <li>
 Familiar with API testing.
 </li>
 <li>
 Comfortable using scripting languages like Python, JavaScript, or Java.
 </li>
 <li>
 Experience with tools such as Selenium or Postman is a plus.
 </li>
 <li>
 Any exposure to NLP (intent recognition, entity extraction, conversational flows) is a plus!
 </li>
 <li>
 Basic knowledge of QA methods and development tools (version control, issue tracking, test coverage).
 </li>
 <li>
 Strong problem-solving and attention to detail, able to work independently while communicating clearly with the team, and fluent in English (written and spoken).
 
 
 </li>
 </ul>
 We&rsquo;re Siemens. A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit and business need. Bring your curiosity and creativity and help us shape tomorrow!
 
 
 Siemens is an equal opportunities employer and do not discriminate unlawfully on any grounds. We are committed to providing access and equal opportunity.
</div>

AI QA Engineer

2070Health

<div>**This is not a role with 2070 Health** 
Role Title: QA Engineer &mdash; AI Native and Agentic Systems
 
Location: Remote across India (works US Pacific hours) 
Type: Full-time
About the Company: 
Zenara Health is a technology-driven mental health care company dedicated to transforming access and quality of mental wellness services. The company combines AI-powered platforms with expert clinical care to deliver personalized, effective mental health solutions. Zenara Health strives to innovate and improve mental health outcomes by connecting patients and providers through a seamless digital experience.
About the role:
This Is Not a Traditional QA Role
This is not a transitional or maintenance QA position.
We are building agentic software development, and we need QA that operates at the same speed, intelligence, and autonomy as development.
You will design and own an AI-driven QA system that:
<ul><li>Tests complex SaaS products end-to-end
</li><li>Discovers bugs autonomously (without hand-written test cases)
</li><li>Simulates how a new human QA engineer would deeply explore the product
</li><li>Runs continuously (ideally 24&times; 7)
</li><li>Integrates directly into agentic development loops
</li></ul>If your idea of QA is mostly writing Selenium scripts from requirements, this role is not for you.
The Mission
Build and operate an autonomous QA engine that:
&bull; Thinks like a human QA engineer &bull;
Acts like an AI system
<ul><li>Never sleeps
</li><li>And never lets defects escape
</li></ul>QA here is not a gate at the end &mdash; it is a real-time adversary to development agents until quality is proven.
What You Will Own (End-to-End)
1. Autonomous, AI-Driven QA
Design AI-based systems that:
<ul><li>Explore UI, APIs, workflows, and edge cases without pre-defined scripts
</li><li>Generate and execute tests dynamically from product behavior
</li><li>Discover bugs through exploration, not just assertions
</li><li>Move beyond static automation into self-directed testing systems
</li></ul>2. Agentic QA &times; Agentic Development Integration
Build QA agents that:
<ul><li>Continuously test features as development agents build them
</li><li>Provide structured, actionable feedback in real time
</li><li>Loop with development agents until quality thresholds are met
</li><li>Own the QA feedback loop as a first-class system, not a manual process
</li></ul>3. Full-Stack Quality Coverage
Validate quality across:
<ul><li>Web UI
</li><li>Backend services
</li><li>APIs
</li><li>Data integrity
</li><li>End-to-end user journeys
</li><li>Ensure the system works as a cohesive product, not just isolated components
</li></ul>4. Intelligent Defect Discovery &amp; Verification
Automatically identify:
<ul><li>Functional defects
</li><li>Workflow breaks
</li><li>Regression issues
</li><li>Performance and reliability risks
</li><li>Ensure issues are:
</li><li>Reproducible
</li><li>Verified
</li><li>Clearly explainable to humans</li></ul>
5. Continuous, Always-On QA
<ul><li>QA does not stop at &ldquo;test execution&rdquo;
</li><li>Build systems that:
</li><li>Run continuously
</li><li>Adapt as the product evolves
</li><li>Increase coverage automatically over time
</li></ul>6. Quality Ownership
<ul><li>Define what &ldquo;release-ready&rdquo; means
</li><li>Block releases when quality is insufficient &mdash; with evidence
</li><li>Raise risks early, clearly, and decisively
</li></ul>What Success Looks Like
<ul><li>Bugs are found before humans see them
</li><li>QA coverage grows without linear human effort
</li><li>Development speed increases because QA is faster
</li><li>QA agents actively challenge dev agents
</li><li>Releases feel boring &mdash; because nothing breaks</li></ul>
Schedule
Daytime hours with 4&ndash;8 hours of overlap to US Pacific, with flexibility for critical releases or audits.
Requirements
Who You Are
You think of QA as a system design problem, not a checklist.
You&rsquo;re excited by:
<ul><li>Autonomous systems
</li><li>AI-driven exploration
</li><li>Replacing manual effort with intelligence
</li><li>Designing feedback loops, not just test suites
</li></ul>You&rsquo;re uncomfortable with:
<ul><li>Manually writing hundreds of brittle test cases
</li><li>QA that reacts instead of anticipates
</li><li>Automation that breaks every sprint
</li></ul>Required Experience
<ul><li>3+ years in QA (manual + automation) &mdash; foundation matters
</li></ul>Strong understanding of:
<ul><li>SDLC
</li><li>Test strategies
</li><li>Failure modes in complex SaaS systems
</li></ul>Hands-on experience with:
<ul><li>UI automation (Playwright / Cypress / Selenium)
</li><li>API testing Demonstrated use of AI in QA beyond basic test generation
</li></ul>&bull; Autonomous testing &bull; AI-assisted exploratory testing
<ul><li>Intelligent test orchestration
</li><li>Ability to explain how AI systems decide what to test next
</li></ul>Strongly Preferred:<ul><li>Experience designing QA frameworks or platforms
</li><li>Experience integrating QA into CI/CD at a system level
</li></ul>&bull; Performance / reliability testing &bull; Healthcare or regulated systems experience
<ul><li>Prior work where QA influenced architecture decision</li></ul>
Benefits
Benefits
Remote-first
Equipment stipend
Local holidays (India)
Learning budget (QA, security, cloud, AI tools)</div>

QA Engineer - AI Native and Agentic Systems - Zenara Health

Deutsche Bank

<div><h2 class="jobSectionHeader">Job Description:
</h2>Job Title: QA Automation Engineer / Senior QA Automation Engineer (AI Platforms), AVP
Location: Pune, India
Role Description
The QA Automation Engineer ensures quality, reliability, and stability of AI-powered applications and platforms. The role involves designing automation frameworks, validating machine-learning&ndash;driven outputs, and ensuring consistent performance of both traditional and AI-driven systems. You will work with developers, data scientists, ML engineers, and product teams to build robust test strategies that validate model behavior, data quality, and AI user experiences.
What we&rsquo;ll offer you
As part of our flexible scheme, here are just some of the benefits that you&rsquo;ll enjoy
<ul><li>Best in class leave policy
</li><li>Gender neutral parental leaves
</li><li>100% reimbursement under childcare assistance benefit (gender neutral)
</li><li>Sponsorship for Industry relevant certifications and education
</li><li>Employee Assistance Program for you and your family members
</li><li>Comprehensive Hospitalization Insurance for you and your dependents
</li><li>Accident and Term life Insurance
</li><li>Complementary Health screening for 35 yrs. and above
</li></ul>Your key responsibilities
Core QA Responsibilities
<ul><li>Design and maintain automation frameworks for UI, API, and backend testing.
</li><li>Develop test automation scripts using Selenium, Playwright, Cypress, or similar.
</li><li>Build API automation suites using RestAssured, Postman/Newman, etc.
</li><li>Perform test planning, execution, reporting, and defect lifecycle management.
</li><li>Implement automated tests in CI/CD pipelines (Jenkins, TeamCity, GitHub Actions).
</li><li>Perform root-cause analysis and support L3 production issues.
</li></ul>AI-Focused QA Responsibilities
<ul><li>Collaborate with Data Science and ML teams to test AI/ML model behavior.
</li><li>Validate model outputs for accuracy, precision, recall, thresholds, and stability.
</li><li>Test AI-driven features: recommendations, NLP/chatbots, classification, anomaly detection, predictive insights, etc.
</li><li>Automate validation of model inference APIs, streaming outputs, and batch pipelines.
</li><li>Conduct data-quality testing for ML feature inputs (schema, drift, distribution checks).
</li><li>Validate model retraining, deployment workflows, and versioning pipelines.
</li><li>Test UI interfaces showing model predictions, confidence scores, and explainability outputs.
</li><li>Ensure fairness, bias detection, and responsible AI presentation in product workflows.
</li><li>Collaborate with MLOps to test end-to-end ML lifecycle.
</li></ul>Tools &amp; Frameworks for AI Model Testing
<ul><li>AI/ML Testing Frameworks
</li><li>Deepchecks &ndash; ML model validation, data integrity, drift checks
</li><li>DeepEval / TruEra / Arthur AI &ndash; model evaluation, quality monitoring, bias &amp; fairness checks
</li><li>Evidently AI &ndash; automated monitoring for model drift, data drift, data quality
</li><li>Fiddler AI &ndash; model explainability, fairness, performance dashboards
</li><li>MLflow &ndash; model validation, experiment tracking, test comparison
</li><li>Great Expectations &ndash; data validation for ML pipelines
</li></ul>Data &amp; Pipeline Testing
<ul><li>PyTest + custom ML test harnesses
</li><li>Soda Data / Deequ &ndash; data quality checks for ML features
</li><li>Airflow/Kubeflow test modules &ndash; pipeline DAG testing
</li></ul>Model Inference / API Testing Tools
<ul><li>Postman/Newman &ndash; testing ML inference endpoints
</li><li>RestAssured &ndash; API-based model validation
</li><li>Locust/JMeter &ndash; load testing of inference throughput &amp; latency
</li></ul>Observability &amp; Monitoring Tools
<ul><li>Prometheus + Grafana &ndash; monitoring inference latency &amp; performance
</li><li>Elastic Stack (ELK) &ndash; logging of model behavior &amp; anomalies
</li><li>OpenTelemetry &ndash; tracing AI pipeline performance
</li></ul>Your skills and experience
Test automation using Selenium, Playwright, Cypress, or equivalent.
<ul><li>Strong programming/scripting in Python, Java, or JavaScript.
</li><li>Framework design experience (POM, Hybrid, BDD, Data-Driven).
</li><li>Strong background in API testing.
</li><li>Experience with ML/AI testing frameworks (Evidently, Deepchecks, MLflow, Fiddler, GE).
</li><li>Understanding of ML workflows, model metrics, and data validation.
</li><li>Experience with cloud platforms and containers.
</li></ul>Soft Skills
<ul><li>Strong analytical and debugging skills.
</li><li>Attention to detail and quality mindset.
</li><li>Ability to collaborate with engineering, AI, and product teams.
</li><li>Clear communication skills; ability to explain ML test findings.
</li></ul>How we&rsquo;ll support you
<ul><li>Training and development to help you excel in your career
</li><li>Coaching and support from experts in your team
</li><li>A culture of continuous learning to aid progression
</li><li>A range of flexible benefits that you can tailor to suit your needs
</li></ul>About us and our teams
Please visit our company website for further information:
https://www.db.com/company/company.html
We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.
<div><div><div><div>Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.
We welcome applications from all people and promote a positive, fair and inclusive work environment.</div></div></div></div></div>

QA Automation Engineer / Senior QA Automation Engineer (AI Platforms), AVP

E2M Solutions Inc.

About E2M:E2M Solutions works as a trusted white-label partner for digital agencies. We support agencies with consistent and reliable delivery through services such as website design, web development, ecommerce, SEO, AI SEO, PPC, AI automation, and content writing. Founded on strong business ethics, we are an equal opportunity organization powered by 300+ experienced professionals, partnering with 400+ digital agencies across the US, UK, Canada, Europe, and Australia. At E2M, we value ownership, consistency, and people who are committed to doing meaningful work and growing together. If you&rsquo;re someone who dreams big and has the gumption to make them come true, E2M has a place for you. Job SummaryWe are looking for a dedicated AI/ML Quality Assurance Engineer who will be responsible for ensuring the quality and reliability of AI/ML solutions, models, and intelligent systems. You will develop and execute test plans, validate model performance, collaborate with AI developers, and automate testing where applicable.Key Responsibilities:<ul><li>Design, develop, and execute comprehensive test plans and test cases for AI/ML models and AI-enabled applications (functional, non-functional, regression, performance)</li><li>Validate AI model accuracy, stability, robustness, fairness, and reliability under diverse scenarios</li><li>Collaborate closely with AI engineers / data scientists to understand model behaviour and requirements</li><li>Automate validation workflows using scripting languages/tools</li><li>Track, investigate, and report issues/defects; work with developers for root-cause analysis</li><li>Ensure end-to-end testing of data pipelines feeding AI system</li><li>Contribute to continuous improvement of the AI QA framework and standards</li><li>Create test documentation, results reports, and QA metrics dashboards</li><li>Participate in planning and QA strategy discussions</li></ul>Required Skills &amp; Qualifications:Technical Skills:<ul><li>Bachelor&rsquo;s degree in Computer Science, IT, Engineering, or related field.</li><li>3+ years overall QA experience (manual + automation; preferably including AI systems)</li><li>At least 1 year of hands-on experience with AI/ML system testing or AI solutions</li><li>Familiarity with automation tools (Selenium, PyTest, JUnit, or similar)</li><li>Knowledge of version control (Git), CI/CD principles, test management tools</li><li>Understanding of data validation, model evaluation metrics, bias/fairness checks</li></ul>Soft Skills:<ul><li>Strong analytical and problem-solving ability</li><li>Excellent communication and collaboration skills</li><li>Detail-oriented, proactive in eliminating defects early</li><li>Ability to work in cross-functional teams</li></ul>Nice-to-Have:<ul><li>Experience in automated model testing frameworks</li><li>Knowledge of NLP, computer vision, or deep learning testing</li><li>Experience with cloud platforms (AWS / GCP / Azure)</li><li>Certifications in AI/ML or QA (ISTQB, AI certification etc.)</li></ul>Job Types: Full-time, PermanentPay: ₹600,000.00 - ₹700,000.00 per yearBenefits:<ul><li>Health insurance</li><li>Paid sick time</li><li>Provident Fund</li></ul>Work Location: In person

AI/ML Quality Assurance Engineer

Deeplight

<div>DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.
The QA &amp; Application Testing &amp; Automation Engineer is responsible for the quality, resilience, and performance of the Bank&rsquo;s digital and core operational platforms. This role goes beyond traditional testing, focusing on the end-to-end validation of next-generation AI systems, mobile applications, and enterprise services. By building sophisticated automated frameworks and continuous testing pipelines, you will ensure that every release&mdash;from Conversational AI agents to core banking microservices&mdash;meets the highest standards of security, scalability, and reliability. You will act as a quality gatekeeper, collaborating across engineering and cybersecurity teams to accelerate deployment without compromising the Bank's integrity.
Your responsibilities within this role include:
<ul><li>Validate next-gen AI platforms (voice and chat) for accuracy, stability, latency, and safety; ensure AI-driven enterprise search avoids hallucinations.</li><li>
Build and maintain reusable automation frameworks for web, mobile, and API integrations using Python, Selenium, or Playwright.</li><li>
Validate RAG (Retrieval-Augmented Generation) pipelines, vector search quality, and grounding accuracy to ensure data retrieval performance.</li><li>
Implement automated quality checks for MLOps, including drift detection, retraining validation, and model registry integrity.</li><li>
Conduct scenario-based testing for operational AI agents (KYC, Risk, Compliance) and validate high availability and disaster recovery protocols.</li><li>
Integrate automated quality gates into CI/CD pipelines to ensure continuous validation within containerized (Docker/Kubernetes) environments.</li><li>
Verify that all AI engineering aligns with guardrails for fairness, security, explainability, and regulatory requirements.</li></ul>
As an AI consultancy, our greatest asset is the expertise of our people. 
 
While technical mastery is the foundation of what we do, the ability to bridge the gap between complex data science and actionable business value is what defines your success with Deeplight. 
 
We're looking for individuals who are not only world-class in their fields of specialism, but also compelling communicators and persuasive advocates for their own skills. 
 
You will be the face of our firm, tasked with building trust, articulating the &quot;why&quot; behind your technical decisions, and effectively &quot;selling&quot; your vision to high-level stakeholders. 
 
If you thrive on the challenge of presenting cutting-edge solutions as much as you do on building them, you will fit right in. 
Requirements 
We need you to have:<ul><li>
A Bachelor&rsquo;s degree in Computer Science, AI, Software Engineering, or a related quantitative field. A Master&rsquo;s degree in AI/ML is highly preferred.</li><li>
A minimum 5+ years in QA and Automation, preferably within a large-scale digital bank or a major digital transformation project.</li><li>
Proven experience deploying AI/ML QA solutions at an enterprise scale, specifically in banking or financial services.</li><li>
Deep knowledge of software testing methodologies (Functional, Regression, Security, and Non-functional).</li><li>
Proficiency in Python for test automation and expertise with tools like PyTest, Selenium, Playwright, and Postman.</li><li>
Hands-on experience testing LLM response quality, prompt stability, and agentic orchestration workflows.</li><li>
Strong experience validating pipelines and storage services across Azure (AI Foundry) and AWS (SageMaker).</li><li>
Proficiency in load and stress testing using tools like JMeter or Locust.</li><li>
Expertise in SQL and NoSQL test validation (Postgres, MongoDB, Cassandra) and data platform integrity.</li></ul>
It would be beneficial if you also have:<ul><li>
The ability to evaluate and integrate emerging AI testing tools such as LangChain, CrewAI, or Bedrock.</li><li>
Experience at acting as an &quot;analytics translator&quot; between technical teams and business stakeholders regarding quality risks.</li><li>
An understanding of cybersecurity principles in the context of AI safety and prompt injection prevention.</li><li>
A proven ability to work within fast-paced squads to remove blockers and manage dependencies.</li></ul> 
Benefits 
Benefits &amp; Growth Opportunities:<ul><li>
Competitive salary.</li><li>
Visa Sponsorship for the successful individual.
</li><li>Comprehensive health insurance for the successful individual.
</li><li>Professional development and certification support.</li><li>
Opportunity to work on cutting-edge AI projects.</li><li>
Career advancement opportunities in a rapidly growing AI company.</li></ul>
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.
At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.
Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.
If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.</div>

QA & Application Testing & Automation Engineer

Cubitrek Private Limited

We are looking for a detail-oriented QA Engineer to join our growing team and help ensure the highest quality standards for our AI-powered knowledge retention platform. If you are passionate about testing modern SaaS applications and enjoy working with cutting-edge AI products, we would love to hear from you.About the Role As a QA Engineer, you will be responsible for designing and executing test strategies, identifying bugs, and ensuring smooth functionality across our platform. You will collaborate closely with developers, product managers, and AI teams to maintain product reliability and performance.ResponsibilitiesDevelop and execute manual and automated test casesPerform functional, regression, integration, and performance testingIdentify, document, and track bugs and usability issuesCollaborate with development teams to resolve defectsTest API integrations and third-party integrationsEnsure product quality across web applications and cloud environmentsParticipate in sprint planning, reviews, and QA documentationRequirements2+ years of experience in QA or software testingStrong understanding of software QA methodologies and testing processesExperience with manual and automation testing toolsFamiliarity with API testing tools (Postman, REST clients, etc.)Experience working with SaaS or web-based applicationsStrong analytical and problem-solving skillsGood communication and documentation skillsNice to HaveExperience testing AI/ML based applicationsKnowledge of cloud platforms (AWS, Azure, or GCP)Experience with CI/CD pipelinesFamiliarity with automation frameworks like Selenium, Cypress, or PlaywrightWhat We OfferOpportunity to work on an innovative AI productCollaborative and growth-focused environmentCompetitive salary and career development opportunitiesJob Type: Full-timeExperience:<ul><li>QA or Software Testing: 2 years (Required)</li></ul>Work Location: In person

QA Engineer

<div>
 
 Your IT Future, Delivered.
 
 
 
 
 Software Engineer
 
 
 
 With a global team of 5600+ IT professionals, DHL IT Services connects people and keeps the global economy running by continuously innovating and creating sustainable digital solutions. We work beyond global borders and push boundaries across all dimensions of logistics. You can leave your mark shaping the technology backbone of the biggest logistics company of the world. All our offices have earned #GreatPlaceToWork certification, reflecting our commitment to exceptional employee experiences.
 
 
 
 Digitalization. Simply delivered.
 
 
 
 At IT Services, we are passionate about building high‑quality software backed by strong engineering and quality practices. No matter your level of DevOps engineer proficiency, you can always grow within our diverse environment.
 
 
 
 #DHL #DHLITServices #GreatPlace
 
 
 
 
 Grow together.
 
 
 
 As a Software engineer, you will design and develop Java-based applications while contributing to quality validation through functional/QA activities. You will also support the team in exploring and adopting AI/GenAI tools and models to improve engineering productivity and product capabilities.
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Java Development
 
 
 
 
 <ul>
 <li>
 Design, develop, and maintain Java-based applications following clean coding standards.
 </li>
 <li>
 Collaborate with architects, product owners, and other developers to understand business requirements.
 </li>
 <li>
 Participate in code reviews, refactoring, and performance improvements.
 </li>
 <li>
 Contribute to technical design discussions and propose innovative solutions.
 
 
 
 </li>
 </ul>
 
 Quality Assurance (Non-Automation)
 
 
 
 
 <ul>
 <li>
 Perform functional, integration, system, and regression testing for Java-based applications.
 </li>
 <li>
 Create and maintain test scenarios, test cases, and test data.
 </li>
 <li>
 Validate application behavior across releases and ensure alignment with requirements.
 </li>
 <li>
 Log defects, participate in triage discussions, and support teams until closure.
 </li>
 <li>
 Ensure adherence to QA best practices and contribute to improving QA processes.
 
 
 
 </li>
 </ul>
 
 AI / GenAI
 
 
 
 
 <ul>
 <li>
 Support the team in exploring AI/GenAI tools and capabilities relevant to development and QA.
 </li>
 <li>
 Work with AI-based assistants, code generation tools, and intelligent test-case generation aids.
 </li>
 <li>
 Participate in pilot initiatives involving LLMs, prompt engineering, AI-assisted code review, or similar technologies.
 </li>
 <li>
 Contribute ideas on how AI can enhance developer productivity and quality outcomes.
 
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 
 Core Technical
 
 
 
 
 <ul>
 <li>
 Strong proficiency in Core Java, OOP concepts, and Java application development.
 </li>
 <li>
 Experience with Spring/Spring Boot (webflux) is an mandatory.
 </li>
 <li>
 Strong understanding of relational databases and writing SQL queries.
 </li>
 <li>
 Familiarity with Git or other version control systems.
 
 
 
 </li>
 </ul>
 
 QA Skills (Manual)
 
 
 
 
 <ul>
 <li>
 Hands-on experience in manual functional testing for web applications.
 </li>
 <li>
 Ability to design test cases, test scenarios, and perform root-cause validation.
 </li>
 <li>
 Good understanding of SDLC, STLC, and defect lifecycle.
 </li>
 <li>
 Exposure to tools such as JIRA, QTest, or similar.
 
 
 
 </li>
 </ul>
 
 AI / GenAI Exposure
 
 
 
 
 <ul>
 <li>
 Understanding of Large Language Models (LLMs) and GenAI concepts.
 </li>
 <li>
 Experience using AI tools for development or QA (e.g., AI coding copilots, AI test-case generation).
 </li>
 <li>
 Awareness of prompt engineering basics is a plus.
 
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 
 <ul>
 <li>
 Familiarity with microservices or REST API concepts.
 </li>
 <li>
 Basic understanding of cloud environments (AWS/Azure/GCP).
 </li>
 <li>
 Experience working in Agile/Scrum teams.
 
 
 
 </li>
 </ul>
 
 An array of benefits for you:
 
 
 
 
 <ul>
 <li>
 Hybrid work arrangements to balance in-office collaboration and home flexibility.
 </li>
 <li>
 Annual Leave: 42 days off apart from Public / National Holidays.
 </li>
 <li>
 Medical Insurance: Self + Spouse + 2 children. An option to opt for Voluntary Parental Insurance (Parents / Parent -in-laws) at a nominal premium covering pre existing disease.
 </li>
 <li>
 In House training programs: professional and technical training certifications.
 </li>
 </ul>
</div>

Software Engineer

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