Test Manager

🏢 Summary: Full-time DevOps/SRE role focused on automating and optimizing the Software Development Lifecycle, including CI/CD pipelines, build and release processes, and developer infrastructure. The position aims to improve integration speed, reliability, and collaboration by advancing trunk-based development and modern DevOps practices. You will work closely with development and SRE teams to enhance automation, infrastructure, and software delivery performance. 🗂️ Requirements: 6+ years in DevOps or SRE in Software or SaaS environment, Strong Linux systems administration experience, Proficiency in Bash, Python or Perl scripting, Experience with Git and branching strategies, Hands-on experience with CI/CD systems, Experience with trunk-based development practices, Strong knowledge of Docker and Kubernetes, Experience with Terraform and Ansible, Experience automating build and release processes, Understanding of DevOps and SRE principles, Experience managing CI infrastructure and developer tooling 📃 Skills: Linux, Bash, Python, Perl, Git, GitLab, GitHub, Jenkins, ArgoCD, Docker, Kubernetes, Terraform, Ansible, CI/CD, SonarQube, Ontrack 🏢 Description: Job description Company Description At CluePoints, we’re redefining how clinical trials are run. As the premier provider of Risk-Based Quality Management (RBQM) and Data Quality Oversight software, we harness advanced statistics, artificial intelligence, and machine learning to ensure the quality, accuracy, and integrity of clinical trial data, helping life sciences organizations bring safer, more effective treatments to patients faster. We’re proud to be an ambitious, fast-growing technology scale-up with a dynamic and diverse international team representing more than 20 nationalities. Collaboration, flexibility, and continuous learning are part of our DNA. At CluePoints, you’ll find a culture where you can grow, make an impact, and have fun along the way.Guided by our values of Care, Passion, and Smart Disruption , we’re united by a shared mission: to create smarter ways to run efficient clinical trials and deliver AI-powered insights that improve human outcomes worldwide. The Role In this role, you’ll work at the heart of our Software Development Lifecycle (SDLC) automation efforts. You’ll be responsible for improving how we integrate, build, and release code — ensuring that developers can deliver value quickly and safely. This role is ideal for someone passionate about DevOps practices, automation, and enabling developer productivity at scale. (We cannot consider B2B Contractors for this Position) - Full time Permanent Employee applications will be considered for this vacancy. Job requirements What You’ll Bring 6+ years of experience in a DevOps or SRE role in a Software or SaaS environment Strong experience with Linux systems administration Proficiency in scripting languages (e.g., Bash, Python, or Perl) Solid experience with Git and branching strategies , with a focus on improving collaboration and enabling high-frequency integration Strong experience with CI/CD systems (e.g., GitLab CI, GitHub Actions, Jenkins, ArgoCD) and building reliable, fast feedback pipelines Good understanding of modern CI practices , including frequent integration, maintaining a stable main branch, and reducing merge complexity Experience supporting or working in environments moving toward trunk-based development (e.g., short-lived branches, incremental changes) Deep understanding of containerization tools (Docker) and orchestration (Kubernetes) Experience with infrastructure-as-code and automation tools (Terraform, Ansible) Strong understanding of DevOps principles: automation, feedback loops, and shift-left testing Experience automating software build and release processes A strong grasp of software integration workflows, dependency management, and production readiness Understanding of SRE principles and how reliability and infrastructure practices support software delivery Ability to work cross-functionally and guide teams toward improved engineering practices Job responsibilities What You’ll Be Doing Design, build, and maintain shared CI/CD pipeline templates and automation tools with a focus on fast feedback and reliable integration Develop and support internal tools for build, test, and release automation Collaborate with development teams to improve how code is integrated, tested, and prepared for production Help define and evolve best practices for source control, branching strategies, and code collaboration , supporting a move toward trunk-based development Guide teams in adopting incremental, high-quality changes that reduce risk and improve delivery flow Partner with SRE teams to align deployment strategies, observability, and infrastructure practices with application delivery Manage, optimize, and monitor developer infrastructure (CI runners, SonarQube, Ontrack, artifact repositories, etc.) Drive improvements in release readiness, code quality, and testing practices across teams Identify and remove bottlenecks in the software delivery lifecycle , improving speed without compromising reliability Continuously evaluate new tools and technologies to improve our platform and developer experience Job benefits 🇬🇧 What We Offer – United Kingdom Private Medical Insurance through Vitality Health (full hospital cover, 24/7 GP, and therapy sessions) Group Critical Illness Cover with Aviva Life Insurance (death-in-service lump sum) Pension Scheme with 9% employer contribution via Scottish Widows Opportunities for professional development and sponsored certifications A hub-based hybrid model that blends flexibility with purpose — connecting teams through collaboration, learning, and a vibrant social culture. 🇬🇧 Equal Opportunities & Data Protection Statement CluePoints is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and applicants. We welcome applications from all individuals regardless of age, disability, gender identity or expression, marital or civil partnership status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. Any personal data you share during your application will be processed in accordance with the UK GDPR and the Data Protection Act 2018 and will be used solely for recruitment purposes. By submitting your application, you consent to the processing of your data for recruitment and employment purposes.

🏢 Summary: Site Reliability Engineer focused on Observability and Real User Monitoring, responsible for enhancing end-to-end telemetry across frontend, backend, and Kubernetes environments. The role combines core SRE practices with ownership of monitoring, logging, tracing, alerting, and user-experience metrics in production. It involves evolving observability tooling, improving incident detection, and supporting reliable, data-driven operations. 🗂️ Requirements: 5+ years experience in SRE, DevOps, Platform Engineering or Observability roles, Hands-on experience with observability and monitoring platforms, Experience implementing Real User Monitoring (RUM) in production, Experience with frontend and application observability, Experience working with Azure and Kubernetes environments, Ability to define and manage SLIs and SLOs, Experience with incident detection, alerting and production troubleshooting, Experience evaluating managed vs self-managed observability solutions 📃 Skills: Azure, Kubernetes, Elastic, Grafana, Prometheus, OpenTelemetry, Sentry, APM, RUM, SLI, SLO, JavaScript, LangChain, LangGraph, OpenAI, Anthropic 🏢 Description: Job description Company Description At CluePoints, we’re redefining how clinical trials are run. As the premier provider of Risk-Based Quality Management (RBQM) and Data Quality Oversight software, we harness advanced statistics, artificial intelligence, and machine learning to ensure the quality, accuracy, and integrity of clinical trial data, helping life sciences organizations bring safer, more effective treatments to patients faster. We’re proud to be an ambitious, fast-growing technology scale-up with a dynamic and diverse international team representing more than 20 nationalities. Collaboration, flexibility, and continuous learning are part of our DNA. At CluePoints, you’ll find a culture where you can grow, make an impact, and have fun along the way.Guided by our values of Care, Passion, and Smart Disruption , we’re united by a shared mission: to create smarter ways to run efficient clinical trials and deliver AI-powered insights that improve human outcomes worldwide. Role: The Site Reliability Engineer, Observability & RUM is responsible for improving end-to-end observability across our platforms and customer-facing applications, with a particular focus on frontend and Real User Monitoring (RUM). This role combines core SRE practices with ownership of monitoring, logging, tracing, alerting, and user-experience telemetry in production. You will help evolve our observability capabilities across Azure and Kubernetes environments, improve incident detection and diagnosis, and support decisions around managed versus self-managed observability tooling. You will partner closely with Engineering, Support, QA, and Security teams to ensure systems ship with actionable telemetry, dashboards, alerts, and operational runbooks. Job requirements 5+ years of experience in Site Reliability Engineering, DevOps, Platform Engineering, or Observability Engineering roles. Strong hands-on experience with observability and monitoring platforms, including several of the following:Elastic, Grafana, Prometheus, OpenTelemetry, Sentry, monitoring agents, and managed APM/observability platforms. Experience implementing and supporting Real User Monitoring (RUM) and frontend/application observability in production environments. Ability to work across frontend, backend, and platform teams to improve telemetry, alerting, and incident diagnosis. Experience evaluating or operating managed observability platforms and understanding the trade-offs versus self-managed stacks. (Nice to have) Experience supporting ML, AI, or LLM-backed services in production (RAG, LangSmith, Arize Phoenix, LangChain, LangGraph, Azure OpenAI, OpenAI, or Anthropic APIs). Job responsibilities Own and improveReal User Monitoring (RUM) for customer-facing applications, including browser performance, client-side errors, user journeys, and frontend service dependencies. Partner with frontend, product, and engineering teams to improve visibility into user experience, JavaScript/runtime failures, page performance, and customer-impacting issues. Establish and maintain end-to-end observabilityacross frontend, backend, infrastructure, and Kubernetes environments using metrics, logs, traces, dashboards, and alerting. Evaluate, implement, and operate managed and self-managed observability solutions, helping guide the evolution of the observability stack. Support and improve observability tooling such as Sentry, Elastic, Grafana, Prometheus, OpenTelemetry, monitoring agents, and related APM platforms. Define and maintain SLIs, SLOs, and alerting strategies that improve service reliability, reduce noise, and enable faster detection of production issues. Lead or support incident detection, alert triage, live production troubleshooting, and service restoration across outage, latency, batch, file transfer, and degradation scenarios, in partnership with Support and Production teams. Job benefits 🇵🇱 What We Offer – Poland Comprehensive Health Insurance (medical, dental, and online consultations, 100% employee coverage) Life Insurance through UNUM Cafeteria Plan with flexible monthly credits for wellness, entertainment, and travel MultiSport Card , co-financed 50/50 Employee Capital Plans (PPK) with 4% employer contribution A hub-based hybrid model that blends flexibility with purpose — connecting teams through collaboration, learning, and a vibrant social culture. Equal Opportunities & Data Privacy Statement CluePoints is an equal opportunity employer committed to diversity and inclusion in the workplace. Your personal data will be processed by CluePoints for recruitment purposes in accordance with the Regulation (EU) 2016/679 (GDPR). If you wish for your data to be retained for future opportunities, please include the following statement in your CV: “I consent to the processing of my personal data by CluePoints for the purposes of future recruitment processes.”

🏢 Summary: The role focuses on leading AI-driven transformation of enterprise QA by implementing advanced automation frameworks, predictive quality insights, and modern testing strategies. It aims to modernize quality engineering across complex ERP, e-commerce, and cloud-native environments while integrating continuous testing into CI/CD pipelines. The position drives innovation, efficiency, and strategic value through AI-enabled QA practices. 🗂️ Requirements: 8+ years of QA experience, Hands-on experience with automation frameworks, Experience with AI-driven testing tools, Experience with large-scale enterprise systems, Ability to implement AI-assisted QA and predictive testing, Experience with continuous testing and CI/CD integration, Experience with ERP, e-commerce, and cloud-native applications, Ability to define QA metrics and predictive quality insights, Experience leading QA modernization initiatives 📃 Skills: AI, Automation, CI/CD, ERP, E-commerce, Cloud, PredictiveAnalytics, Playwright, MCP, Cursor, SDLC, RegressionTesting 🏢 Description: Project overview This project focuses on modernizing enterprise-level QA through AI-driven frameworks, predictive quality insights, and automation strategies. The initiative brings innovation to complex integrated environments, moving QA toward a strategic, value-driven function while improving efficiency and delivery accuracy. Team You will collaborate with enterprise QA specialists, automation engineers, architects, and client stakeholders. The team works in a cross-functional environment with a strong focus on continuous improvement, knowledge sharing, and modern QA practices. Position overview We are looking for an Enterprise QA Innovation Lead who will drive AI-enabled transformation across enterprise QA engagements and elevate quality engineering to a strategic, innovation-focused discipline. Technology stack AI-assisted testing tools, automation frameworks, ERP systems, e-commerce platforms, cloud native applications, CI/CD pipelines, predictive analytics, and modern QA toolsets Responsibilities Lead the design and implementation of AI-driven QA frameworks that optimize test coverage, detect anomalies, and generate predictive quality insights Drive process innovation across enterprise QA engagements, identifying opportunities to reduce manual effort, accelerate delivery, and standardize QA practices Collaborate with enterprise clients, internal QA teams, and engineering teams to integrate modern QA methodologies into the SDLC, including shift left, continuous testing, and CI/CD pipelines Develop and deploy advanced automation strategies, leveraging AI-assisted test generation and intelligent regression testing for ERP, e-commerce, and cloud native applications Define metrics and analytics frameworks to monitor QA efficiency, automation ROI, defect trends, and predictive quality indicators Evaluate and introduce emerging QA technologies, AI-driven tools, and best practices for enterprise software quality Act as a strategic innovation partner to enterprise clients, shaping QA approaches for complex environments and delivering measurable business value Lead QA modernization initiatives across enterprise accounts, focusing on process efficiency, automation, and predictive QA adoption Requirements 8 years of QA experience, including hands-on experience with automation frameworks, AI-driven testing, and large-scale enterprise systems Demonstrated ability to implement AI-assisted QA tools, predictive QA, and continuous testing strategies Background in optimizing QA processes for ERP, e-commerce, and cloud native applications Strong analytical and problem-solving skills with experience defining QA metrics and predictive insights Experience collaborating with enterprise clients and internal teams to implement innovative QA solutions Strong communication skills with the ability to convey technical innovation and strategic QA improvements to stakeholders Nice to have Experience with AI testing tools such as Playwright MCP, Cursor, or similar Background in QA digital transformation initiatives

🏢 Summary: The offer is for a Test/Quality Engineer to drive quality engineering practices within a DevOps environment, focusing on risk-based testing, preventive defect strategies, and advanced test automation integrated into CI/CD pipelines. The role includes building quality gates, implementing non-functional testing, and modernizing the Test & Quality stack with AI-driven improvements. It emphasizes end-to-end ownership of quality across the software delivery lifecycle. 🗂️ Requirements: Bachelor’s degree in Computer Science, Software Quality Engineering or related field, or equivalent experience, Minimum 5 years of experience in software quality engineering, Experience as QA/Test Engineer in Agile/DevOps environments, Hands-on experience with automated testing at unit, API, integration, and UI/E2E levels, Experience integrating automated tests into CI/CD pipelines, Proficiency in at least one programming or scripting language, Knowledge of DevSecOps practices including SAST and DAST, Experience designing test strategies and defining quality gates and metrics, Understanding of testing pyramid and risk-based testing approach, Experience with non-functional testing (performance, security, reliability), Experience with Agentic IDEs and agent-assisted testing workflows, Experience with automated visual validation and Design Tokens 📃 Skills: Playwright, Cypress, Selenium, REST, Java, C#, Python, JavaScript, TypeScript, Azure, GitHub, GitLab, CI/CD, SAST, DAST, DevOps, DevSecOps, AI, FMEA 🏢 Description: Project Context We are looking for a Test/Quality Engineer to join our DevOps team and drive a quality engineering mindset across the delivery lifecycle. You will focus on risk-based testing, failure scenario analysis, preventive defect practices, and high-impact automation integrated into CI/CD. You will also contribute to the business case and roadmap for modernizing our Test & Quality stack—including opportunities enabled by AI—to improve speed, reliability, and cost efficiency. Goals and Deliverables Key Responsibilities Design and implement automated tests at multiple levels (unit, API/contract, integration, UI, end-to-end) and ensure they run reliably in CI/CD. Embed quality engineering practices into DevOps delivery (shift-left and shift-right) with a focus on prevention over detection. Perform risk analysis and define test strategies based on business impact, critical user journeys, and failure scenarios (FMEA-style thinking). Build and maintain quality gates in pipelines (test execution, coverage thresholds, static analysis, vulnerability checks, artifact promotion rules). Improve testability and quality-by-design with engineering teams (observability, feature flags, resilient design, dependency mocking/service virtualization). Establish and monitor quality metrics (defect escape rate, flaky test rate, pipeline health, lead time to detect, MTTR contributors). Drive continuous improvement of test frameworks, tooling, and environments (test data, environment readiness, parallelization, execution time). Implement non-functional testing practices where relevant (performance, reliability, security testing coordination). Contribute to the Test & Quality transformation roadmap, including identifying where AI can accelerate: test design, test maintenance, defect triage, log analysis, and documentation. Identify and implement opportunities for automation and process improvements. Key Requirements Bachelor's degree in Computer Science, Software Quality Engineering, or a related field, or equivalent practical experience. 5 years of professional experience in software quality engineering. (e.g., 3+ years for mid-level, 5+ for senior) Proven experience as a QA/Test Engineer or Quality Engineer in Agile/DevOps environments. Strong quality engineering mindset: risk-based testing, preventive defect approach, and failure-mode thinking. Hands-on test automation experience (one or more of: Playwright, Cypress, Selenium; plus API automation with REST tools/frameworks). Familiarity with DevSecOps practices (SAST/DAST, dependency scanning) and secure testing fundamentals. Proficiency in at least one programming/scripting language used for automation (e.g., Java, C#, Python, JavaScript/TypeScript). Practical CI/CD experience (Azure DevOps, GitHub Actions, Gitlab pipelines or equivalent) including pipeline integration of automated tests. Experience designing test strategies and defining quality gates and metrics. Strong understanding of testing concepts across the pyramid (unit → integration → E2E) and how to optimize for speed and stability. Proficiency with Agentic IDEs and experience with "Agent in the loop" workflows for automatic testing and quality testing. Experience reading Design Tokens and ensuring the UI code matches the source of truth through automated visual validation. Other Details This position is focused on driving quality within a progressive DevOps environment and includes opportunities to work with cutting-edge technologies in test automation and AI. The role offers flexibility regarding remote work arrangements.

🏢 Summary: The offer is for a QA Lead responsible for defining and executing the overall quality strategy within Agile environments. The role combines hands-on backend validation with leadership of distributed QA teams and full ownership of testing processes. It requires deep integration of QA practices into SDLC/STLC and coordination of both manual and automated testing efforts. 🗂️ Requirements: Proven experience leading QA teams and quality processes, Proficiency in SQL, Proficiency in Linux, Hands-on experience working in Agile environments, Experience with defect tracking and reporting using JIRA and Xray, Experience integrating QA within SDLC/STLC processes 📃 Skills: SQL, Linux, Agile, JIRA, Xray, SDLC, STLC, Playwright, RobotFramework, Azure, Kafka, Git, CI/CD, ISTQB 🏢 Description: Your Responsibilities Quality Ownership: Defining QA strategy, quality standards, and the roadmap. Test Design: Designing risk-based tests and maintaining full test documentation. Leadership: Leading, mentoring, and coordinating work within distributed teams. Process Integration: Deeply embedding QA into the SDLC/STLC and Agile workflows. Execution: Coordinating manual and automated testing efforts. Management: Handling defect tracking and reporting via JIRA and Xray. Requirements (Must-have) Leadership Experience: Proven track record in leading QA teams and quality processes. Backend Skills: Proficiency in SQL and Linux for system validation. Agile Expertise: Practical, hands-on experience in Agile environments. Communication: Strong ability to communicate with both technical and business stakeholders. Nice to Have Automation: Experience with Playwright or Robot Framework . Modern Tech: Knowledge of Microsoft Azure , Apache Kafka , and Git . DevOps: Understanding of CI/CD pipelines. Certification: ISTQB .

🏢 Summary: Lead AI Testing Engineer role focused on defining and automating QA strategies for AI-driven systems, knowledge graphs, ontologies and RAG-based LLM applications. The position involves building scalable test frameworks, validating data-heavy systems, integrating quality gates into CI/CD pipelines and ensuring end-to-end quality across backend, frontend and AI layers. Candidates will work with graph technologies, GenAI evaluation frameworks and automation-first testing practices. 🗂️ Requirements: 8+ years of experience in software development, test automation and DevOps, Python test automation with pytest or equivalent, Experience with AI/ML library integration, Knowledge Graph or Data Ontology testing experience, OWL2, RDF, SPARQL, SHACL validation, GraphDB experience, QA strategy design for complex data-heavy systems, SQL and graph query language validation, Cypher, Backend and REST API testing, Frontend test automation with Playwright or equivalent, Experience with coding agents and agentic development, RAG-based Gen AI / LLM testing and evaluation, Gen AI / LLM evaluation frameworks and metrics, Automation of Gen AI/RAG evaluation at scale, Agile delivery experience, Git, Azure DevOps or JIRA, English proficiency B2 or higher 📃 Skills: Python, pytest, OWL2, RDF, SPARQL, SHACL, GraphDB, SQL, Cypher, REST, Playwright, RAG, LLM, Git, Azure, JIRA, Postman, Bruno, Jenkins, CI/CD 🏢 Description: We are looking for a Lead AI Testing Engineer to drive the quality strategy for AI-driven and data migration initiatives spanning knowledge graphs, ontologies and RAG-based LLM features. You will define and execute QA practices across data ingestion, graph layers, rule evaluation engines and AI/LLM components while building automation frameworks that scale evaluation across complex, data-heavy systems. Responsibilities Design and automate evaluation of RAG-based and LLM-driven features including grounding, answer accuracy, determinism/reproducibility, precision, recall and hallucination rate Build test harnesses to scale evaluation beyond human-in-the-loop processes Create data-driven test suites for underwriting rules and validate rule execution via SPARQL evaluator, arithmetic/threshold logic and multi-condition scenarios Verify ontology schema correctness and instance accuracy against source data, perform reasoner consistency checks and SHACL validation Define and drive end-to-end QA strategy covering data ingestion, ontology/graph layer, rule evaluation engine, AI/LLM layer and integration with underwriting solutions Establish quality gates, acceptance criteria and test coverage models Maintain automation test suites across knowledge graph, data ontology layer, backend services and frontend layers Validate end-to-end flows across ontology, rule engine and decision output, perform contract testing and cross-system data consistency validation Integrate test suites into CI/CD pipelines and define release quality gates Champion automation-first and shift-left quality practices Leverage agentic AI and Gen AI tooling in testing and framework development Requirements 8+ years of experience in software development, testing automation and DevOps Proficiency in Python test automation using pytest or equivalent, scripting and AI/ML library integration Expertise in testing Knowledge Graph or Data Ontology solutions using OWL2, RDF and SPARQL Skills in SHACL validation and graph databases such as GraphDB, including ontology validation, entity/relationship integrity, reasoner consistency checks and graph query correctness Proven ability to define and drive QA strategy independently for complex data-heavy systems, including building automation frameworks and implementing quality gates Skills in data validation using SQL and graph query languages such as SPARQL and Cypher, along with understanding of deterministic vs probabilistic systems Background in backend and API testing (REST) covering data validation, integration and E2E testing Proficiency in frontend web application test automation using Playwright or equivalent Python-compatible framework Hands-on experience using coding agents and agentic development daily Demonstrated experience testing and evaluating RAG-based Gen AI / LLM applications including grounding, answer accuracy and hallucination/determinism checks Applied knowledge of Gen AI / LLM evaluation frameworks and metrics such as precision, recall, criteria recall and efficiency, with proven ability to automate Gen AI/RAG evaluation at scale Experience in Agile delivery using Git and Azure DevOps or JIRA English proficiency at B2 level or higher Nice to have Skills in semantic search testing and evaluation Familiarity with Vector Database integration and retrieval validation Background in data science covering ML concepts, data pipelines or data engineering collaboration Proficiency in API tooling such as Postman and Bruno Experience with quality-gate implementation in CI/CD pipelines such as Azure DevOps or Jenkins We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Lead AI Testing Engineer role focused on defining and automating QA strategy for AI-driven, knowledge graph, ontology, and RAG-based LLM systems. The position involves building scalable test frameworks, validating graph and ontology data, and integrating automated quality gates into CI/CD pipelines across backend, frontend, and AI layers. Candidates should have strong expertise in Python automation, semantic technologies, GenAI evaluation, and end-to-end testing for complex data-heavy systems. 🗂️ Requirements: 8+ years in software development, test automation and DevOps, Proficiency in Python test automation, Experience with pytest or equivalent frameworks, Expertise in OWL2, RDF and SPARQL, Experience testing Knowledge Graph or Data Ontology solutions, Skills in SHACL validation, Experience with GraphDB or graph databases, Ability to define QA strategy for complex data-heavy systems, Experience building automation frameworks and quality gates, Skills in SQL, SPARQL and Cypher, Experience with REST API testing, Experience with frontend automation using Playwright or equivalent, Hands-on experience with coding agents and agentic development, Experience testing RAG-based GenAI and LLM applications, Knowledge of GenAI/LLM evaluation metrics, Ability to automate GenAI/RAG evaluation at scale, Experience with Git and Azure DevOps or JIRA, English proficiency at B2 level or higher 📃 Skills: Python, pytest, OWL2, RDF, SPARQL, SHACL, GraphDB, SQL, Cypher, REST, Playwright, Git, JIRA, Azure, Jenkins, Postman, Bruno, LLM, RAG, GenAI, CI/CD 🏢 Description: We are looking for a Lead AI Testing Engineer to drive the quality strategy for AI-driven and data migration initiatives spanning knowledge graphs, ontologies and RAG-based LLM features. You will define and execute QA practices across data ingestion, graph layers, rule evaluation engines and AI/LLM components while building automation frameworks that scale evaluation across complex, data-heavy systems. Responsibilities Design and automate evaluation of RAG-based and LLM-driven features including grounding, answer accuracy, determinism/reproducibility, precision, recall and hallucination rate Build test harnesses to scale evaluation beyond human-in-the-loop processes Create data-driven test suites for underwriting rules and validate rule execution via SPARQL evaluator, arithmetic/threshold logic and multi-condition scenarios Verify ontology schema correctness and instance accuracy against source data, perform reasoner consistency checks and SHACL validation Define and drive end-to-end QA strategy covering data ingestion, ontology/graph layer, rule evaluation engine, AI/LLM layer and integration with underwriting solutions Establish quality gates, acceptance criteria and test coverage models Maintain automation test suites across knowledge graph, data ontology layer, backend services and frontend layers Validate end-to-end flows across ontology, rule engine and decision output, perform contract testing and cross-system data consistency validation Integrate test suites into CI/CD pipelines and define release quality gates Champion automation-first and shift-left quality practices Leverage agentic AI and Gen AI tooling in testing and framework development Requirements 8+ years of experience in software development, testing automation and DevOps Proficiency in Python test automation using pytest or equivalent, scripting and AI/ML library integration Expertise in testing Knowledge Graph or Data Ontology solutions using OWL2, RDF and SPARQL Skills in SHACL validation and graph databases such as GraphDB, including ontology validation, entity/relationship integrity, reasoner consistency checks and graph query correctness Proven ability to define and drive QA strategy independently for complex data-heavy systems, including building automation frameworks and implementing quality gates Skills in data validation using SQL and graph query languages such as SPARQL and Cypher, along with understanding of deterministic vs probabilistic systems Background in backend and API testing (REST) covering data validation, integration and E2E testing Proficiency in frontend web application test automation using Playwright or equivalent Python-compatible framework Hands-on experience using coding agents and agentic development daily Demonstrated experience testing and evaluating RAG-based Gen AI / LLM applications including grounding, answer accuracy and hallucination/determinism checks Applied knowledge of Gen AI / LLM evaluation frameworks and metrics such as precision, recall, criteria recall and efficiency, with proven ability to automate Gen AI/RAG evaluation at scale Experience in Agile delivery using Git and Azure DevOps or JIRA English proficiency at B2 level or higher Nice to have Skills in semantic search testing and evaluation Familiarity with Vector Database integration and retrieval validation Background in data science covering ML concepts, data pipelines or data engineering collaboration Proficiency in API tooling such as Postman and Bruno Experience with quality-gate implementation in CI/CD pipelines such as Azure DevOps or Jenkins We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Lead AI Testing Engineer role focused on building and driving QA strategy for AI-driven, knowledge graph, ontology, and RAG-based LLM systems. The position involves automating evaluation frameworks, validating graph and ontology layers, integrating testing into CI/CD pipelines, and ensuring end-to-end quality across backend, frontend, and AI components. The offer includes flexible remote work within Poland, professional development programs, certifications, and comprehensive benefits. 🗂️ Requirements: 8+ years of experience in software development, test automation and DevOps, Python test automation with pytest or equivalent, Experience with AI/ML library integration, Knowledge Graph or Data Ontology testing experience, OWL2, RDF, SPARQL, SHACL validation, GraphDB experience, SQL data validation, Cypher query language, REST API testing, Frontend test automation with Playwright or equivalent, Experience testing RAG-based Gen AI / LLM applications, Knowledge of Gen AI / LLM evaluation metrics, Automation framework development experience, CI/CD pipeline integration, Agile delivery experience, Git, Azure DevOps or JIRA, English proficiency at B2 level or higher, Hands-on experience with coding agents and agentic development 📃 Skills: Python, pytest, OWL2, RDF, SPARQL, SHACL, GraphDB, SQL, Cypher, REST, Playwright, Git, Azure, JIRA, Jenkins, Postman, Bruno, LLM, RAG, GenAI, CI/CD 🏢 Description: We are looking for a Lead AI Testing Engineer to drive the quality strategy for AI-driven and data migration initiatives spanning knowledge graphs, ontologies and RAG-based LLM features. You will define and execute QA practices across data ingestion, graph layers, rule evaluation engines and AI/LLM components while building automation frameworks that scale evaluation across complex, data-heavy systems. Responsibilities Design and automate evaluation of RAG-based and LLM-driven features including grounding, answer accuracy, determinism/reproducibility, precision, recall and hallucination rate Build test harnesses to scale evaluation beyond human-in-the-loop processes Create data-driven test suites for underwriting rules and validate rule execution via SPARQL evaluator, arithmetic/threshold logic and multi-condition scenarios Verify ontology schema correctness and instance accuracy against source data, perform reasoner consistency checks and SHACL validation Define and drive end-to-end QA strategy covering data ingestion, ontology/graph layer, rule evaluation engine, AI/LLM layer and integration with underwriting solutions Establish quality gates, acceptance criteria and test coverage models Maintain automation test suites across knowledge graph, data ontology layer, backend services and frontend layers Validate end-to-end flows across ontology, rule engine and decision output, perform contract testing and cross-system data consistency validation Integrate test suites into CI/CD pipelines and define release quality gates Champion automation-first and shift-left quality practices Leverage agentic AI and Gen AI tooling in testing and framework development Requirements 8+ years of experience in software development, testing automation and DevOps Proficiency in Python test automation using pytest or equivalent, scripting and AI/ML library integration Expertise in testing Knowledge Graph or Data Ontology solutions using OWL2, RDF and SPARQL Skills in SHACL validation and graph databases such as GraphDB, including ontology validation, entity/relationship integrity, reasoner consistency checks and graph query correctness Proven ability to define and drive QA strategy independently for complex data-heavy systems, including building automation frameworks and implementing quality gates Skills in data validation using SQL and graph query languages such as SPARQL and Cypher, along with understanding of deterministic vs probabilistic systems Background in backend and API testing (REST) covering data validation, integration and E2E testing Proficiency in frontend web application test automation using Playwright or equivalent Python-compatible framework Hands-on experience using coding agents and agentic development daily Demonstrated experience testing and evaluating RAG-based Gen AI / LLM applications including grounding, answer accuracy and hallucination/determinism checks Applied knowledge of Gen AI / LLM evaluation frameworks and metrics such as precision, recall, criteria recall and efficiency, with proven ability to automate Gen AI/RAG evaluation at scale Experience in Agile delivery using Git and Azure DevOps or JIRA English proficiency at B2 level or higher Nice to have Skills in semantic search testing and evaluation Familiarity with Vector Database integration and retrieval validation Background in data science covering ML concepts, data pipelines or data engineering collaboration Proficiency in API tooling such as Postman and Bruno Experience with quality-gate implementation in CI/CD pipelines such as Azure DevOps or Jenkins We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Lead AI Testing Engineer role focused on defining and automating QA strategy for AI-driven, RAG-based LLM, knowledge graph, and data ontology systems. The position involves building scalable automation frameworks, validating complex data and rule-engine workflows, and integrating quality processes into CI/CD pipelines. Candidates will work across backend, frontend, graph databases, and AI evaluation frameworks in large-scale data-heavy environments. 🗂️ Requirements: 8+ years of experience in software development, test automation and DevOps, Proficiency in Python test automation, Experience with pytest or equivalent frameworks, Expertise in OWL2, RDF and SPARQL, Experience testing Knowledge Graph or Data Ontology solutions, Skills in SHACL validation, Experience with GraphDB or similar graph databases, Ability to define and drive QA strategy independently, Experience building automation frameworks and quality gates, Skills in SQL, SPARQL and Cypher, Experience with REST API testing, Experience with frontend automation using Playwright or equivalent, Hands-on experience with coding agents and agentic development, Experience testing RAG-based Gen AI and LLM applications, Knowledge of Gen AI and LLM evaluation metrics, Experience automating Gen AI/RAG evaluation at scale, Experience with Git and Azure DevOps or JIRA, English proficiency at B2 level or higher 📃 Skills: Python, pytest, OWL2, RDF, SPARQL, SHACL, GraphDB, SQL, Cypher, REST, Playwright, Git, Azure, JIRA, LLM, RAG, GenAI, CI/CD, Jenkins, Postman, Bruno 🏢 Description: We are looking for a Lead AI Testing Engineer to drive the quality strategy for AI-driven and data migration initiatives spanning knowledge graphs, ontologies and RAG-based LLM features. You will define and execute QA practices across data ingestion, graph layers, rule evaluation engines and AI/LLM components while building automation frameworks that scale evaluation across complex, data-heavy systems. Responsibilities Design and automate evaluation of RAG-based and LLM-driven features including grounding, answer accuracy, determinism/reproducibility, precision, recall and hallucination rate Build test harnesses to scale evaluation beyond human-in-the-loop processes Create data-driven test suites for underwriting rules and validate rule execution via SPARQL evaluator, arithmetic/threshold logic and multi-condition scenarios Verify ontology schema correctness and instance accuracy against source data, perform reasoner consistency checks and SHACL validation Define and drive end-to-end QA strategy covering data ingestion, ontology/graph layer, rule evaluation engine, AI/LLM layer and integration with underwriting solutions Establish quality gates, acceptance criteria and test coverage models Maintain automation test suites across knowledge graph, data ontology layer, backend services and frontend layers Validate end-to-end flows across ontology, rule engine and decision output, perform contract testing and cross-system data consistency validation Integrate test suites into CI/CD pipelines and define release quality gates Champion automation-first and shift-left quality practices Leverage agentic AI and Gen AI tooling in testing and framework development Requirements 8+ years of experience in software development, testing automation and DevOps Proficiency in Python test automation using pytest or equivalent, scripting and AI/ML library integration Expertise in testing Knowledge Graph or Data Ontology solutions using OWL2, RDF and SPARQL Skills in SHACL validation and graph databases such as GraphDB, including ontology validation, entity/relationship integrity, reasoner consistency checks and graph query correctness Proven ability to define and drive QA strategy independently for complex data-heavy systems, including building automation frameworks and implementing quality gates Skills in data validation using SQL and graph query languages such as SPARQL and Cypher, along with understanding of deterministic vs probabilistic systems Background in backend and API testing (REST) covering data validation, integration and E2E testing Proficiency in frontend web application test automation using Playwright or equivalent Python-compatible framework Hands-on experience using coding agents and agentic development daily Demonstrated experience testing and evaluating RAG-based Gen AI / LLM applications including grounding, answer accuracy and hallucination/determinism checks Applied knowledge of Gen AI / LLM evaluation frameworks and metrics such as precision, recall, criteria recall and efficiency, with proven ability to automate Gen AI/RAG evaluation at scale Experience in Agile delivery using Git and Azure DevOps or JIRA English proficiency at B2 level or higher Nice to have Skills in semantic search testing and evaluation Familiarity with Vector Database integration and retrieval validation Background in data science covering ML concepts, data pipelines or data engineering collaboration Proficiency in API tooling such as Postman and Bruno Experience with quality-gate implementation in CI/CD pipelines such as Azure DevOps or Jenkins We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Lead AI Testing Engineer role focused on defining QA strategy and automation for AI-driven systems, knowledge graphs, ontologies and RAG-based LLM applications. The position covers end-to-end testing across data ingestion, graph layers, rule engines, backend/frontend services and CI/CD pipelines using automation-first practices. Candidates will work on scalable evaluation frameworks for GenAI features, data validation and complex enterprise integrations. 🗂️ Requirements: 8+ years of experience in software development, test automation and DevOps, Proficiency in Python test automation, Experience with pytest or equivalent framework, Expertise in Knowledge Graph or Data Ontology testing, Knowledge of OWL2, Knowledge of RDF, Knowledge of SPARQL, Experience with SHACL validation, Experience with GraphDB or similar graph databases, Ability to define and drive QA strategy independently, Experience building automation frameworks and quality gates, Skills in SQL and graph query languages, Understanding of deterministic and probabilistic systems, Experience in backend and REST API testing, Experience in frontend test automation using Playwright or equivalent, Hands-on experience with coding agents and agentic development, Experience testing RAG-based GenAI and LLM applications, Knowledge of GenAI/LLM evaluation frameworks and metrics, Experience automating GenAI/RAG evaluation at scale, Experience with Agile delivery, Knowledge of Git, Experience with Azure DevOps or JIRA, English proficiency at B2 level or higher 📃 Skills: Python, pytest, OWL2, RDF, SPARQL, SHACL, GraphDB, SQL, Cypher, REST, Playwright, Git, Azure, JIRA, Jenkins, Postman, Bruno, RAG, LLM, GenAI, CI/CD 🏢 Description: We are looking for a Lead AI Testing Engineer to drive the quality strategy for AI-driven and data migration initiatives spanning knowledge graphs, ontologies and RAG-based LLM features. You will define and execute QA practices across data ingestion, graph layers, rule evaluation engines and AI/LLM components while building automation frameworks that scale evaluation across complex, data-heavy systems. Responsibilities Design and automate evaluation of RAG-based and LLM-driven features including grounding, answer accuracy, determinism/reproducibility, precision, recall and hallucination rate Build test harnesses to scale evaluation beyond human-in-the-loop processes Create data-driven test suites for underwriting rules and validate rule execution via SPARQL evaluator, arithmetic/threshold logic and multi-condition scenarios Verify ontology schema correctness and instance accuracy against source data, perform reasoner consistency checks and SHACL validation Define and drive end-to-end QA strategy covering data ingestion, ontology/graph layer, rule evaluation engine, AI/LLM layer and integration with underwriting solutions Establish quality gates, acceptance criteria and test coverage models Maintain automation test suites across knowledge graph, data ontology layer, backend services and frontend layers Validate end-to-end flows across ontology, rule engine and decision output, perform contract testing and cross-system data consistency validation Integrate test suites into CI/CD pipelines and define release quality gates Champion automation-first and shift-left quality practices Leverage agentic AI and Gen AI tooling in testing and framework development Requirements 8+ years of experience in software development, testing automation and DevOps Proficiency in Python test automation using pytest or equivalent, scripting and AI/ML library integration Expertise in testing Knowledge Graph or Data Ontology solutions using OWL2, RDF and SPARQL Skills in SHACL validation and graph databases such as GraphDB, including ontology validation, entity/relationship integrity, reasoner consistency checks and graph query correctness Proven ability to define and drive QA strategy independently for complex data-heavy systems, including building automation frameworks and implementing quality gates Skills in data validation using SQL and graph query languages such as SPARQL and Cypher, along with understanding of deterministic vs probabilistic systems Background in backend and API testing (REST) covering data validation, integration and E2E testing Proficiency in frontend web application test automation using Playwright or equivalent Python-compatible framework Hands-on experience using coding agents and agentic development daily Demonstrated experience testing and evaluating RAG-based Gen AI / LLM applications including grounding, answer accuracy and hallucination/determinism checks Applied knowledge of Gen AI / LLM evaluation frameworks and metrics such as precision, recall, criteria recall and efficiency, with proven ability to automate Gen AI/RAG evaluation at scale Experience in Agile delivery using Git and Azure DevOps or JIRA English proficiency at B2 level or higher Nice to have Skills in semantic search testing and evaluation Familiarity with Vector Database integration and retrieval validation Background in data science covering ML concepts, data pipelines or data engineering collaboration Proficiency in API tooling such as Postman and Bruno Experience with quality-gate implementation in CI/CD pipelines such as Azure DevOps or Jenkins We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.