AI Quality Engineer at Techjays · Remote, Coimbatore · 2 - 10 years · Profitable · Remote friendly · Posted 6 Nov 2026
Machine Learning (ML)TECHJAYS
THE AI REIMAGINATION COMPANY
AI Quality Engineer
Position : AI Quality Engineer
Experience : 3–10 Years
Location : Coimbatore / Hybrid
Joining : Immediate / Within 30 Days
Primary SkillsManual & Functional Testing, AI/ML Application Testing, LLM Testing, Prompt Testing, Test Case Design, API Testing, Regression Testing, Defect Management
Preferred SkillsRAG Testing, Chatbot Testing, AI Response Evaluation, Selenium, Playwright, Cypress, Python, JavaScript, SQL, Postman, JIRA, BDD
About Techjays
At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing intelligent, scalable, and production-grade AI solutions that solve real-world business challenges.
Our global team brings together experienced technology professionals from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build AI-powered applications, intelligent automation platforms, and enterprise software solutions.
We're looking for an AI Quality Engineer with strong functional testing expertise and prior hands-on experience testing AI/ML-powered applications.
This role goes beyond traditional software testing. You will be responsible for validating the quality, accuracy, reliability, and behaviour of AI-powered features, ensuring that intelligent applications perform consistently across different scenarios and real-world use cases.
The ideal candidate should understand both traditional QA methodologies and the unique testing challenges associated with AI systems, including non-deterministic outputs, prompt behaviour, hallucinations, response relevance, and edge-case validation.
Prior hands-on experience testing AI/ML-based products or applications is mandatory. Candidates with only traditional manual testing experience and no AI project exposure will not be a fit.
Key Responsibilities
1. AI Application & LLM Testing
- Perform functional and quality testing of AI-powered applications, LLM-based products, chatbots, and intelligent automation systems.
- Design test scenarios to validate AI-generated responses for accuracy, relevance, consistency, completeness, and contextual understanding.
- Test prompts, prompt variations, and conversational flows to identify unexpected outputs and behavioural inconsistencies.
- Evaluate AI responses for hallucinations, incorrect information, irrelevant answers, and context retention issues.
- Validate AI application behaviour across different user inputs, edge cases, and complex scenarios.
- Test RAG-based applications by validating document retrieval, response relevance, contextual accuracy, and source grounding.
- Evaluate AI-powered search, recommendation engines, and other intelligent product features.
- Collaborate with AI engineers and data science teams to define acceptance criteria and quality benchmarks.
2. Functional & Manual Testing
- Analyse business and technical requirements and convert them into comprehensive test scenarios and test cases.
- Execute functional, regression, integration, system, and user acceptance testing across web and mobile applications.
- Validate end-to-end application workflows, business logic, user interactions, and data processing.
- Identify functional gaps, unexpected behaviour, and usability issues.
- Perform exploratory testing to uncover defects that may not be covered by predefined test cases.
- Ensure application functionality remains stable across different releases and environments.
- Review requirements early in the development lifecycle to identify potential quality risks.
3. AI Quality Evaluation & Validation
- Develop structured testing approaches for non-deterministic AI outputs using behaviour-based, range-based, and scenario-based validation.
- Evaluate AI response quality against expected outcomes and predefined acceptance criteria.
- Validate prompt sensitivity, context handling, conversation memory, and multi-turn interactions.
- Identify failure patterns involving hallucinations, prompt injection, incorrect retrieval, and inconsistent responses.
- Test AI system performance across different input formats, languages, and user scenarios where applicable.
- Maintain test datasets and evaluation scenarios for repeatable AI quality assessment.
- Work with engineering teams to identify root causes of AI-related defects and verify fixes.
4. API & Integration Testing
- Perform manual API testing using Postman or similar tools.
- Validate API request and response structures, status codes, authentication, authorization, and error handling.
- Test integrations between AI services, backend systems, databases, and external APIs.
- Validate data flow between application components and identify integration issues.
- Test API behaviour under different input conditions, including invalid inputs and boundary cases.
- Verify API responses and ensure consistency between frontend and backend functionality.
5. Defect Management & Quality Reporting
- Identify, document, track, and manage defects throughout the testing lifecycle.
- Maintain detailed test cases, test execution reports, defect logs, and test documentation.
- Collaborate with developers to reproduce issues, analyse root causes, and validate fixes.
- Track test coverage, defect trends, and application quality metrics.
- Communicate release risks, unresolved defects, and testing status to relevant stakeholders.
- Participate in release readiness reviews and provide quality sign-off for assigned modules.
6. Automation & Continuous Improvement
- Identify repetitive test scenarios that can be automated to improve testing efficiency.
- Support automation initiatives using Selenium, Playwright, or Cypress.
- Work with developers to improve testability and integrate testing practices into CI/CD workflows.
- Explore AI-assisted testing tools and approaches to improve test coverage and efficiency.
- Continuously improve testing methodologies for both conventional software applications and AI-powered systems.
Required Skills & Experience
1. Functional & Manual QA
- 3–5 years of hands-on experience in manual and functional software testing.
- Strong understanding of software testing methodologies, SDLC, STLC, and defect management.
- Experience designing and executing test cases for functional, regression, integration, and end-to-end testing.
- Strong knowledge of Agile/Scrum methodologies and sprint-based QA processes.
- Experience testing web applications, APIs, and mobile applications.
- Ability to analyse requirements and identify functional gaps, edge cases, and potential risks.
2. Mandatory AI/ML Testing Experience
- Prior hands-on experience testing AI/ML-powered applications or products.
- Practical experience testing LLM-based applications, AI chatbots, conversational systems, or intelligent automation features.
- Understanding of prompt testing and evaluating AI-generated responses.
- Ability to validate AI outputs for accuracy, relevance, consistency, and contextual correctness.
- Experience identifying hallucinations, unexpected AI behaviour, and response-quality issues.
- Understanding of AI application workflows, model outputs, and the challenges associated with non-deterministic systems.
- Experience collaborating with AI/ML engineers or data science teams during testing and validation.
3. API & Integration Testing
- Hands-on experience with manual API testing using Postman.
- Understanding of REST APIs, JSON, request/response validation, authentication, and error handling.
- Experience validating integrations between frontend, backend, and external services.
- Basic understanding of database validation and SQL queries.
4. Testing Tools & Technologies
- Experience with JIRA and Confluence for defect tracking and test documentation.
- Familiarity with Postman, SQL, and browser developer tools.
- Understanding of test management and reporting practices.
- Basic knowledge of BDD frameworks such as Cucumber/Gherkin is an advantage.
Preferred Skills
- Experience testing RAG-based applications, including document retrieval and contextual response validation.
- Exposure to vector databases and semantic search testing.
- Familiarity with LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
- Understanding of LLM evaluation frameworks and AI quality assessment methodologies.
- Experience with AI evaluation tools such as Ragas, DeepEval, or similar frameworks.
- Exposure to prompt injection, adversarial testing, and responsible AI validation.
- Working knowledge of Selenium, Playwright, or Cypress.
- Basic scripting knowledge in Python or JavaScript.
- Familiarity with CI/CD pipelines and automated testing practices.
- Exposure to cross-browser testing tools such as BrowserStack or Sauce Labs.
What We're Looking For Beyond Skills
- AI Testing Mindset: Understands that testing AI applications requires more than checking whether a feature works. Can evaluate response quality, accuracy, relevance, and behaviour.
- Analytical Thinking: Ability to identify unusual scenarios, inconsistent outputs, and hidden quality issues.
- Strong QA Fundamentals: Applies structured testing methodologies while adapting them to AI-powered applications.
- Attention to Detail: Documents defects clearly and identifies patterns in application and AI behaviour.
- Ownership: Takes responsibility for testing quality from requirement analysis through release validation.
- Collaboration: Works effectively with developers, AI engineers, product managers, and data science teams.
- Continuous Learning: Interested in exploring emerging AI technologies and evolving testing methodologies.
- Communication: Clearly communicates test results, defect impact, quality risks, and release readiness.
What We Offer
- Competitive compensation aligned with experience and expertise.
- Flexible work environment (Coimbatore office / Hybrid).
- Paid holidays and flexible time off.
- Medical insurance covering self and family, up to ₹4 lakh per person.
- Opportunity to work on real-world AI-powered products and enterprise applications.
- Hands-on exposure to LLMs, RAG systems, agentic AI, and modern AI engineering practices.
- Opportunities to develop expertise in AI quality engineering and automation testing.
- A collaborative, multicultural environment with opportunities for professional growth.
- A culture that values clarity, integrity, ownership, and continuous learning.
Join Techjays
If you're passionate about software quality and have hands-on experience validating AI-powered applications, we'd love to hear from you.
Join us in building reliable, intelligent, and production-ready AI systems.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Techjays
About
Techjays is The AI Reimagination Company — an enterprise AI partner founded by leaders with experience at Google. We don’t just experiment with AI; we build, deploy, and scale production-grade systems that solve real business problems.
Our focus is on industries where impact matters most — manufacturing, logistics, and complex enterprise operations. From intelligent automation to LLM-powered workflows, we design solutions that deliver measurable business outcomes in under 90 days.
With 20+ live AI systems already in production and over $100M in cost savings delivered, our work goes beyond proof of concept — it drives tangible value.
Headquartered in Menlo Park, Techjays operates across seven countries including the USA, India, UAE, UK, Canada, Australia, and Bangladesh — helping global enterprises rethink how they build, operate, and scale with AI at the core.
Tech stack
Amazon Web Services (AWS)
DockerCandid answers by the company
Coimbatore (remote) and Remote options available.
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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
Job Summary
We are looking for an experienced AI Automation Tester with hands-on experience in testing AI-powered products and applications. The ideal candidate should have strong expertise in Playwright automation, along with practical experience in LLM evaluations (Evals), Golden Datasets (Goldens), and AI Observability.
Key Responsibilities
- Design, develop and execute automated test scripts using Playwright.
- Test AI-powered applications, LLM-based products and Generative AI solutions.
- Work on Evals to assess AI response accuracy, relevance, quality and consistency.
- Create, maintain and validate Golden Datasets (Goldens) for benchmarking AI outputs.
- Implement and work with AI Observability to monitor model performance, response quality, latency and failures.
- Perform functional, regression, API and end-to-end testing.
- Identify, report and track defects to ensure product quality and reliability.
Role Overview
We are looking for an experienced professional to evaluate AI-generated responses for conversational AI agents used in travel-related products. The role focuses on assessing response accuracy, relevance, completeness, and quality to improve AI performance.
Key Responsibilities
- Evaluate AI-generated responses against predefined guidelines and quality standards.
- Perform data annotation, labeling, classification, and quality reviews.
- Identify incorrect, misleading, irrelevant, or incomplete responses and potential AI hallucinations.
- Analyze evaluation data to identify recurring errors, quality gaps, and improvement opportunities.
- Track quality metrics, document findings, and recommend improvements.
- Use Excel/Google Sheets and basic SQL, where applicable, to analyze evaluation data.
- Collaborate with AI and Machine Learning teams to improve conversational AI performance.
Required Skills
- 5–8 years of experience in Data Annotation, AI Evaluation, Content Quality, Search Relevance, or Quality Assurance.
- Strong analytical, problem-solving, and attention-to-detail skills.
- Experience applying evaluation guidelines and quality standards consistently.
- Proficiency in Excel or Google Sheets.
- Good written communication and documentation skills.
- Understanding of quality metrics and data analysis.
Good to Have
- Exposure to Generative AI, LLMs, conversational AI, or AI response evaluation.
- Experience with Human-in-the-Loop (HITL), AI training data validation, or hallucination detection.
- Basic SQL knowledge.
- Experience in travel, hospitality, or search quality evaluation.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
JavascriptTotal 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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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
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.
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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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.
PythonAbout Us
Invorto is our Voice AI product, bringing intelligent voice agents to real-world customer and operational use cases. Our voice pipeline is built in Python, running an STT → LLM → TTS architecture on top of the Pipecat framework.
This is a chance to work on hard problems in voice AI — latency, accuracy, naturalness, and reliability — building zero-to-one, owning your area end-to-end, and shipping to production at scale.
Note: This is a customer-facing role, and strong communication skills are essential.
About the Role
We're looking for a Voice AI Research Engineer to join the Invorto team and help build and continuously improve the voice AI systems that power our intelligent voice agents. This role is focused on the specialized craft of voice AI — designing evaluation and automation frameworks that ensure our STT, LLM, and TTS pipeline performs reliably in real-world, production conditions.
What You'll Do
- Design and build automated testing and quality frameworks for our STT → LLM → TTS voice pipeline, built on Pipecat
- Evaluate and benchmark STT, LLM, and TTS/ASR components on accuracy, latency, naturalness, and robustness across accents, languages, and real-world audio conditions
- Work hands-on with STT, TTS, and ASR models — fine-tuning, evaluating, and improving them for production use cases
- Identify failure modes and edge cases across the pipeline (background noise, accents, interruptions, turn-taking, latency, pipeline-stage handoffs) and build systems to catch them before production
- Collaborate closely with engineering to integrate quality checks and automation into the voice agent development lifecycle within the Pipecat-based architecture
- Research and stay current with advances in voice AI, and bring in new techniques, models, and tools to improve pipeline performance
- Work directly with customers to understand real-world voice use cases and translate them into evaluation criteria and quality benchmarks
- Partner with product and engineering to define what "production-grade quality" means for voice agents and drive the team toward it
What We're Looking For
- 4–6 years of experience, with a specialization in voice AI systems and automated quality evaluation
- Hands-on experience with STT (Speech-to-Text), TTS (Text-to-Speech), and ASR (Automatic Speech Recognition) models
- Experience designing and building automated testing/evaluation frameworks for voice or speech systems
- Strong understanding of what drives voice AI quality — accuracy, latency, naturalness, and robustness to real-world variability
- Strong programming skills in Python; familiarity with Pipecat or similar voice pipeline/orchestration frameworks is a plus
- Understanding of STT → LLM → TTS pipeline architectures and the trade-offs involved at each stage
- Research mindset — comfortable exploring new models, techniques, and tools and translating them into practical improvements
- Excellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and validate quality expectations
Position: Test Engineer
Company : Mayura Consultancy Services
Experience: 2 to 4 yrs
Location : Bangalore
Work Location: Work From Home(WFH)
Apply : Please apply using the URL below Once you complete the application form, we will review your profile and get back to you.
Website :
https://www.mayuraconsultancy.com/careers/test-engineer-opening-mcs?r=jlp
MCS is seeking a meticulous and detail-oriented experienced Test Engineer with minimum of 2 Years of relevant experience to join our team. As a Test Engineer, you will play a crucial role in ensuring the highest standards of quality and efficiency in our products or services. Your primary responsibility will be to assess and evaluate processes, identify areas for improvement, and develop strategies to enhance quality across all aspects of our organization.
Responsibilities
- Develop and implement quality assurance standards, procedures, and methodologies to ensure consistency and excellence in our products, services, or processes.
- Conduct comprehensive evaluations and audits of products, services, or processes to identify deviations, defects, or areas of improvement.
- Maintain detailed records of quality assessments, findings, and recommendations.
- Create and update quality documentation, including standard operating procedures.
- Investigate the root causes of quality issues and collaborate with relevant teams to implement corrective and preventive actions.
- Provide guidance and training to teams and employees on quality standards, best practices, and continuous improvement methodologies.
- Establish feedback mechanisms and channels for employees and customers to report quality-related concerns or suggestions for improvement.
- Prepare and deliver regular reports on quality performance, highlighting areas of success and areas requiring attention.
- Ensure that our processes and products adhere to relevant industry standards, regulations, and compliance requirements
- Drive a culture of continuous improvement by identifying opportunities to streamline processes and enhance quality.
Qualifications:
- Bachelor's degree or Master's degree in a relevant field (Quality Management, Business, Engineering, etc.)
- Proven experience of 1-2 years as a Test Engineer.
- Strong analytical and problem-solving skills.
- Proficiency in quality management tools and methodologies (e.g., Six Sigma, Lean, ISO standards).
- Excellent communication skills.
- Attention to detail and a commitment to precision.
- Ability to work collaboratively with cross-functional teams.
- Familiarity with quality management software and tools.
If you have a keen eye for detail, a passion for process improvement, and the ability to drive positive change, we invite you to apply. This role offers the opportunity to make a significant impact on our organization's quality standards and contribute to our ongoing success. Apply today to be a part of our quality-driven team!
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon