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As a Quality Engineer Consultant, you will join a QE team and contribute to testing activities across projects, gaining hands-on experience in software quality assurance. You will support test execution, documentation, and reporting while building your skills in either manual or automated testing. This role is ideal for candidates starting their career in testing, with curiosity and willingness to learn, and who want exposure to modern QA practices, tools, and emerging technologies, including GenAI tools to improve testing efficiency. Responsibilities:<ul><li>Assist in functional and non-functional testing tasks, including executing test cases, logging defects, and reporting results.</li><li>Learn and apply QA processes and best practices under the guidance of more experienced team members.</li><li>Gain exposure to test automation tools and contribute to automated test scripts when appropriate.</li><li>Explore and experiment with GenAI tools to support testing efficiency, defect detection, and test data generation.</li><li>Participate in team discussions, sharing observations, asking questions, and proposing simple improvements.</li><li>Actively engage in learning opportunities, including trainings, workshops, and knowledge-sharing sessions.</li></ul>Requirements&nbsp;To qualify for the role, you must have:&nbsp;<ul><li>Bachelor’s or Master’s degree in Business Administration, Computer Science, Engineering, or a related field.</li><li>1 –2 years of experience in software testing (manual and/or automated) or a strong interest in entering the field. </li><li>Familiarity with manual or automated testing, with willingness to learn both.</li><li>Understanding of QA processes, methodologies, and best practices.</li><li>Basic knowledge of test management or defect tracking tools is desirable.</li><li>ISTQB Foundation Level certification is considered a plus.</li><li>Ability to work collaboratively in a team environment and communicate effectively.</li><li>Excellent problem-solving skills, attention to detail, and the ability to think critically.  </li><li>Experience in Energy sector will be considered a plus.&nbsp;</li><li>Military obligations fulfilled where applicable.&nbsp;&nbsp; &nbsp;</li></ul>Benefits: <ul><li>Competitive remuneration package</li><li>Private health insurance</li><li>Ticket Restaurant card</li><li>Hybrid working model</li><li>Clear opportunities for professional growth and continuous learning</li><li>Access to modern tools, technologies, and best-practice methodologies</li></ul>&nbsp;

Junior QA Engineer Consultant

Our client is a premier software development firm specializing in the delivery of large-scale ICT projects tailored for the public sector. Their company was founded with a mission to transform public services through the strategic implementation of cutting-edge technology. With a profound understanding of the unique needs and challenges faced by government agencies, they are committed to providing solutions that drive efficiency, transparency, and enhanced citizen engagement.Their core services include custom software development, ICT project management, system integration, cybersecurity, cloud solutions, and data analytics. Each service is meticulously designed to meet the specific requirements of public sector organizations.Their company stands out due to their extensive experience and proven track record in the public sector. They have successfully implemented numerous large-scale projects, each driving significant improvements in service delivery and operational efficiency.The role:<ul><li>Developing and delivering high-quality, scalable front-end features using Angular and TypeScript, from concept to deployment</li><li>Producing clean, maintainable, and testable code following best practices and internal standards</li><li>Ensuring high performance and responsiveness of web applications</li><li>Implementing secure coding principles and contributing to code reviews</li><li>Refactoring existing code and optimizing for performance</li><li>Debugging and resolving issues across the full front-end framework</li></ul><h2>Requirements:</h2><ul><li>BSc in Computer Science or a related field</li><li>3-6 years of experience in developing web applications using Angular and TypeScript</li><li>Strong understanding of modern front-end architecture and design patterns</li><li>Experience building scalable, stateless Single Page Applications (SPAs)</li><li>Proficiency in consuming and integrating RESTful APIs</li><li>Experience with version control tools (preferably Git)</li><li>Strong understanding of responsive design and cross-browser compatibility issues</li><li>Ability to work effectively within a collaborative team environment</li></ul>Preferred but not mandatory:<ul><li>Experience with RxJS, NgRx or similar state management libraries</li><li>Familiarity with OWASP web security guidelines</li><li>Experience with Java or .NET environments</li><li>Hands-on experience with agile methodologies and tools like Jira or Azure DevOps</li><li>Knowledge of CI/CD pipelines and automated testing (Jasmine, Karma, Cypress)</li></ul><h2>What they offer:</h2><ul><li>Hybrid working model</li><li>Competitive compensation package</li><li>Continuous professional development and training</li><li>Friendly, dynamic, and collaborative work environment</li><li>Engagement in impactful, large-scale public sector projects</li></ul>

Mid/Senior Angular Developer

Our Client is seeking an Application Support Engineer with experience in operational support of production environments and strong technical understanding of software applications. The ideal candidate will be responsible for monitoring, troubleshooting, and resolving issues related to the performance and operation of critical applications within a 24/7 support framework.Key Responsibilities<ul><li>Monitoring the operation of production applications using monitoring tools. </li><li>Reading and analyzing application logs. </li><li>Administering Kubernetes clusters. </li><li>Collaborating with development teams for debugging and reproducing issues. </li><li>Performing health checks, restarting services, scaling pods. </li><li>Participating in a 24/7 rotating shift schedule. </li><li>Documenting actions and communicating incidents.</li></ul>Required Skills &amp; Experience<ul><li>1–3 years of experience in Application Support / DevOps Support. </li><li>Experience in reading logs. </li><li>Experience with monitoring tools. </li><li>Hands-on experience in Kubernetes administration. </li><li>Understanding of CI/CD, containers, and microservices. </li><li>Strong troubleshooting skills. </li><li>Good knowledge of Linux. </li><li>Good command of the English language.</li></ul>Nice-to-Have Qualifications<ul><li>Experience with ticketing systems. </li><li>Basic SQL knowledge or API troubleshooting experience. </li><li>Team spirit and responsibility.</li></ul>Working Schedule<ul><li>24/7 rotating shifts with shift compensation and the option for remote support.</li></ul>They Offer<ul><li>Participation in high-tech projects. </li><li>Access to modern monitoring &amp; observability tools. </li><li>Continuous training. </li><li>Competitive compensation and benefits package.</li></ul>

Application Support Engineer NEW

Our Client is seeking an experienced Senior AI Engineer&nbsp;with deep expertise in&nbsp;LangChain&nbsp;and modern&nbsp;LLM frameworks. You will lead the development of advanced LLM-driven applications, design complex&nbsp;RAG architectures, and guide the team in best practices for LLM engineering. Key Responsibilities LangChain &amp; LLM Development<ul><li>Design and develop advanced applications using&nbsp;LangChain, LangGraph, and LangSmith</li><li>Build complex&nbsp;chains, agents, and multi-agent systems</li><li>Implement&nbsp;custom tools, retrievers, and memory systems</li><li>Develop context-aware&nbsp;conversational AI and chatbot applications</li><li>Create workflow orchestration using&nbsp;LangGraph&nbsp;for complex reasoning tasks</li><li>Integrate multiple LLM providers (OpenAI, Anthropic, Cohere, Azure OpenAI)</li><li>Optimize&nbsp;prompt templates&nbsp;and&nbsp;output parsers</li></ul>RAG &amp; Vector Database Architecture<ul><li>Design and implement advanced&nbsp;Retrieval-Augmented Generation (RAG)&nbsp;systems</li><li>Develop custom&nbsp;embedding strategies&nbsp;and&nbsp;chunking techniques</li><li>Work with vector databases such as&nbsp;Pinecone, Weaviate, Chroma, Qdrant, Milvus</li><li>Implement&nbsp;hybrid search&nbsp;(semantic + keyword) and&nbsp;reranking&nbsp;methods</li><li>Build document loaders and text splitters for diverse data sources</li><li>Optimize retrieval quality with&nbsp;metadata filtering&nbsp;and&nbsp;query expansion</li><li>Develop&nbsp;multi-modal RAG systems&nbsp;(text, images, documents)</li></ul>Advanced LLM Techniques<ul><li>Apply advanced prompt engineering:&nbsp;few-shot,&nbsp;chain-of-thought,&nbsp;ReAct</li><li>Build&nbsp;function calling&nbsp;and tool-use patterns</li><li>Develop structured output with&nbsp;Pydantic models</li><li>Implement&nbsp;streaming responses&nbsp;and async pipelines</li><li>Build efficient&nbsp;caching strategies&nbsp;for cost optimization</li><li>Implement&nbsp;fallback mechanisms&nbsp;and robust error handling</li><li>Integrate&nbsp;guardrails&nbsp;and content moderation systems</li></ul>Production &amp; Monitoring<ul><li>Deploy LangChain applications to production using&nbsp;LangServe</li><li>Integrate&nbsp;LangSmith&nbsp;for tracing, debugging, and evaluation</li><li>Implement monitoring and observability for LLM applications</li><li>Build evaluation frameworks for quality assurance</li><li>Optimize latency, cost, and token usage</li><li>Run&nbsp;A/B testing&nbsp;for prompt variations</li><li>Create dashboards to monitor key LLM metrics</li></ul>Required Qualifications Education<ul><li>Bachelor’s degree in Computer Science, Machine Learning, or related field (required)</li><li>Master’s degree in AI/ML or Computer Science (preferred)</li></ul>Experience<ul><li>5+ years of software development experience</li><li>3+ years working with AI/ML and LLM applications</li><li>2+ years hands-on experience with&nbsp;LangChain&nbsp;(mandatory)</li><li>Proven experience building&nbsp;production-grade LLM applications</li><li>Strong background with&nbsp;RAG architectures&nbsp;and vector databases</li></ul>Technical Skills – LangChain Ecosystem &nbsp;LangChain Core (Required)<ul><li>Expert-level knowledge of&nbsp;LangChain (v0.1+)</li><li>Deep understanding of Chains, Agents, Tools, Memory, Callbacks</li><li>Experience with&nbsp;LangChain Expression Language (LCEL)</li><li>Knowledge of&nbsp;LangGraph&nbsp;for complex workflows</li><li>Familiarity with&nbsp;LangSmith&nbsp;for monitoring/debugging</li><li>Experience deploying with&nbsp;LangServe</li><li>Understanding of&nbsp;LangChain Templates</li></ul>LLM Providers &amp; APIs<ul><li>Strong experience with&nbsp;OpenAI API&nbsp;(GPT-4, GPT-3.5, embeddings)</li><li>Knowledge of&nbsp;Anthropic Claude API</li><li>Familiarity with&nbsp;Azure OpenAI Service</li><li>Experience with open-source models (Llama, Mistral, Mixtral)</li><li>Knowledge of&nbsp;Hugging Face Inference API</li><li>Understanding model capabilities, limitations, and pricing models</li></ul>Vector Databases &amp; Embeddings<ul><li>Hands-on experience with&nbsp;Pinecone, Weaviate, or Chroma</li><li>Knowledge of embedding models (OpenAI, Cohere, sentence-transformers)</li><li>Understanding similarity search algorithms</li><li>Experience with metadata filtering and hybrid search</li><li>Knowledge of vector indexing strategies (HNSW, IVF)</li></ul>Programming &amp; Software Engineering<ul><li>Expert-level Python (asyncio, type hints, Pydantic)</li><li>Experience with&nbsp;FastAPI</li><li>Strong understanding of async/await patterns</li><li>Strong software engineering fundamentals</li><li>Experience with Git, CI/CD, testing frameworks</li></ul>&nbsp;Cloud &amp; Infrastructure<ul><li>Experience with AWS (Lambda, ECS, S3, DynamoDB) or Azure</li><li>Docker containerization</li><li>Kubernetes (preferred)</li><li>Serverless architectures</li><li>API Gateway and load balancing</li></ul>Core Capabilities<ul><li>Deep understanding of LLM capabilities and limitations</li><li>Expertise in prompt engineering and optimization</li><li>Ability to design scalable LLM architectures</li><li>Strong understanding of cost optimization for LLM workloads</li><li>Knowledge of AI safety and responsible AI practices</li><li>Excellent problem-solving and communication skills</li></ul>Preferred Qualifications<ul><li>Contributions to LangChain or other open-source LLM projects</li><li>Experience with LlamaIndex, Haystack, or similar frameworks</li><li>Knowledge of fine-tuning (LoRA, QLoRA)</li><li>Experience with multi-agent systems and AutoGPT patterns</li><li>Knowledge of semantic caching and query optimization</li><li>Experience with document intelligence and OCR</li><li>Understanding transformer architectures</li><li>Experience with evaluation frameworks (RAGAS, TruLens)</li><li>Experience with streaming and real-time LLM processing</li><li>Blog posts, tutorials, or presentations on LangChain</li><li>Cloud certifications</li></ul>What They Offer<ul><li>Highly competitive salary and equity package</li><li>Full health, dental, and vision insurance</li><li>Generous budget for professional development and certifications</li><li>Flexible working arrangements (remote/hybrid options)</li><li>Access to cutting-edge AI infrastructure and LLM APIs</li><li>Collaborative environment with world-class AI professionals</li><li>Participation in conferences and AI community events</li><li>Opportunities for technical leadership and mentorship</li><li>Influence over the company’s AI strategy</li></ul>&nbsp;Success Metrics Success in this role will be measured by:<ul><li>Quality and performance of LangChain applications</li><li>Reduction in latency and improved cost efficiency</li><li>Accuracy and relevance of RAG systems</li><li>Adoption of best practices across the team</li><li>Speed of delivery for new AI features</li><li>User satisfaction with AI-powered features</li><li>Technical leadership and mentorship impact</li><li>Contribution to documentation and knowledge base</li></ul>Technologies You Will Work With LLM Frameworks<ul><li>LangChain, LangGraph, LangSmith, LangServe</li><li>OpenAI API, Anthropic Claude API</li><li>Hugging Face Transformers</li></ul>Vector Databases<ul><li>Pinecone, Weaviate, Chroma, Qdrant</li><li>PostgreSQL with pgvector</li></ul>Development Stack<ul><li>Python 3.11+, FastAPI, Pydantic</li><li>Docker, Kubernetes</li><li>AWS/Azure cloud services</li><li>Git, GitHub Actions</li></ul>Monitoring &amp; Observability<ul><li>LangSmith</li><li>Prometheus, Grafana</li><li>DataDog, New Relic</li></ul>

AI Engineer – LangChain & LLM Frameworks Specialist

Our Client is seeking a detail-oriented LLM Quality Analyst to join their AI team. You will be responsible for designing, implementing, and managing comprehensive testing and evaluation frameworks for their generative AI products. This role is critical to ensuring their AI systems meet the highest standards of quality, accuracy, safety, and ethical compliance before reaching production.Key ResponsibilitiesTesting Framework Development<ul><li>Design and implement comprehensive testing frameworks for LLM and generative AI applications</li><li>Create curated benchmark suites using industry-standard datasets (TruthfulQA, ARC, TriviaQA, MMLU)</li><li>Develop custom evaluation datasets tailored to specific use cases and domains</li><li>Build synthetic data generation pipelines for edge case testing</li><li>Define clear evaluation criteria, rubrics, and quality metrics</li><li>Establish testing protocols for different AI model types and applications</li></ul>Quality Evaluation &amp; Testing<ul><li>Execute automated and manual evaluations of AI model outputs</li><li>Measure and track key quality metrics: relevance, factual consistency, coherence, hallucination rate</li><li>Assess model performance across dimensions: accuracy, latency, fairness, toxicity, bias</li><li>Perform functional correctness testing for code generation and structured outputs</li><li>Conduct A/B testing and shadow testing for model comparisons</li><li>Validate prompt engineering strategies and RAG pipeline effectiveness</li></ul>Feedback Management &amp; Issue Tracking<ul><li>Manage intake of user-reported issues and feedback</li><li>Translate user feedback into reproducible test cases</li><li>Replicate and document bugs, edge cases, and failure modes</li><li>Log and track defects in issue-tracking systems (Jira, Linear, GitHub Issues)</li><li>Prioritize issues based on severity, frequency, and business impact</li><li>Collaborate with engineering teams on root cause analysis and resolution</li></ul>Human Annotation &amp; LLM-Based Evaluation<ul><li>Coordinate human annotation efforts with clear guidelines and rubrics</li><li>Implement overlapping review processes to ensure annotation consistency</li><li>Integrate LLM-based evaluators (GPT-4, Claude) for automated quality assessment</li><li>Design evaluation prompts that provide structured scores and reasoning</li><li>Validate LLM evaluator outputs against human judgments</li><li>Continuously refine evaluation methodologies based on findings</li></ul>Monitoring &amp; Reporting<ul><li>Monitor live-traffic metrics through observability dashboards</li><li>Track model performance trends and identify quality regressions</li><li>Generate comprehensive quality reports for product and engineering teams</li><li>Present findings and recommendations to stakeholders</li><li>Maintain documentation of testing procedures and evaluation results</li><li>Drive continuous improvement of AI system quality</li></ul>Required QualificationsEducation<ul><li>Bachelor’s degree in Computer Science, Data Science, Linguistics, Cognitive Science, or related field</li><li>Master’s degree in AI/ML, NLP, or related field (preferred)</li></ul>Experience<ul><li>3+ years of experience in quality assurance, testing, or evaluation roles</li><li>2+ years working with AI/ML systems, preferably LLMs or NLP applications</li><li>Experience designing and executing test plans for software or AI products</li><li>Proven track record of identifying and documenting complex technical issues</li></ul>Technical Skills<ul><li>Programming: Proficiency in Python for test automation and data analysis</li><li>LLM Knowledge: Understanding of how LLMs work, their capabilities and limitations</li><li>Evaluation Frameworks: Familiarity with LLM evaluation tools (Langfuse, DeepEval, RAGAS, Phoenix)</li><li>Data Analysis: Experience with pandas, numpy, and data visualization tools</li><li>Testing Tools: Knowledge of pytest, unittest, or similar testing frameworks</li><li>Issue Tracking: Proficiency with Jira, Linear, GitHub Issues, or similar platforms</li><li>APIs: Ability to work with REST APIs and LLM provider APIs (OpenAI, Anthropic)</li><li>SQL: Basic SQL skills for querying databases and analyzing results</li></ul>Quality Assurance Expertise<ul><li>Strong understanding of QA methodologies and best practices</li><li>Experience with test case design and test coverage analysis</li><li>Knowledge of different testing types: functional, regression, integration, performance</li><li>Familiarity with CI/CD pipelines and automated testing integration</li><li>Understanding of metrics and KPIs for quality measurement</li></ul>AI/ML Evaluation Knowledge<ul><li>Understanding of common LLM evaluation metrics (BLEU, ROUGE, BERTScore, perplexity)</li><li>Knowledge of bias detection and fairness evaluation techniques</li><li>Familiarity with hallucination detection and factual consistency checking</li><li>Understanding of prompt engineering and its impact on model outputs</li><li>Awareness of AI safety, ethics, and responsible AI principles</li></ul>Core Competencies<ul><li>Exceptional attention to detail and analytical thinking</li><li>Strong problem-solving and critical reasoning abilities</li><li>Excellent written and verbal communication skills</li><li>Ability to work independently and manage multiple priorities</li><li>Collaborative mindset for cross-functional teamwork</li><li>Curiosity and willingness to learn new AI technologies</li></ul>Preferred Qualifications<ul><li>Experience with specific LLM evaluation platforms (Langfuse, Weights &amp; Biases, Arize)</li><li>Knowledge of human-in-the-loop evaluation workflows</li><li>Familiarity with RAG systems and vector database evaluation</li><li>Experience with adversarial testing and red-teaming for AI systems</li><li>Understanding of model fine-tuning and its quality implications</li><li>Background in linguistics, cognitive science, or human-computer interaction</li><li>Experience with statistical analysis and hypothesis testing</li><li>Knowledge of regulatory requirements (GDPR, AI Act) for AI systems</li><li>Contributions to AI evaluation research or open-source projects</li><li>Experience with multimodal AI evaluation (text, image, audio)</li></ul>What They Offer<ul><li>Competitive salary and benefits package</li><li>Comprehensive health, dental, and vision insurance</li><li>Professional development opportunities in AI/ML</li><li>Flexible work arrangements (remote/hybrid options)</li><li>Access to cutting-edge AI technologies and tools</li><li>Collaborative team environment with AI experts</li><li>Opportunity to shape quality standards for innovative AI products</li><li>Conference attendance and learning budget</li></ul>&nbsp;

AI Engineer (LLM Quality Analyst)

They are seeking an experienced PostgreSQL DBA with strong automation skills using Ansible. The ideal candidate will be responsible for managing, maintaining, and optimizing their PostgreSQL databases, and ensuring efficient and reliable automation for provisioning and maintenance tasks.Key Responsibilities<ul><li>Administer, maintain, and tune PostgreSQL databases in production and non-production environments.</li><li>Set up and maintain replication, backups, and high-availability configurations (e.g., Repmgr, Patroni, pgBackRest, pgbouncer/pgpool ). extra: TimescaleDB, PG vector flavors.</li><li>Develop and maintain Ansible playbooks for PostgreSQL deployments, updates, and configurations.</li><li>Troubleshoot and resolve database-related performance, capacity, and replication issues.</li><li>Collaborate with DevOps and development teams to ensure database reliability and efficiency.</li><li>Perform database upgrades and patching with minimal downtime.</li><li>Implement security best practices and monitor for vulnerabilities.</li><li>Document database environments, processes, and procedures.</li></ul>Required Skills<ul><li>4+ years of hands-on experience as a PostgreSQL DBA in a production environment.</li><li>Solid experience with PostgreSQL versions 14 and above.</li><li>Proficiency in writing and maintaining Ansible playbooks and roles.</li><li>Experience with PostgreSQL performance tuning and optimization.</li><li>Deep understanding of PostgreSQL internals, WAL, autovacuum, and indexes.</li><li>Experience with backup/recovery tools (e.g., pgBackRest, Barman, Commvault).</li><li>Familiarity with monitoring tools (e.g., Prometheus, Dynatrace, pg_stat_statements).</li><li>Linux system administration experience (preferably Debian/Ubuntu or RHEL/CentOS).</li><li>Scripting experience (Bash, Python) is a must.</li><li>Decent in System administration (OS-DB tuning, VIP strategies, systemd logic)</li></ul>Preferred Qualifications:<ul><li>Experience with Kubernetes and PostgreSQL Operators.</li><li>Familiarity with CI/CD pipelines and infrastructure-as-code tools like Terraform.</li><li>PostgreSQL certification or relevant coursework.</li><li>Automation mindset. Eye for details, drive to bring structure and improve standards</li></ul>What They Offer<ul><li>22 annual vacation days, 3 sick days that are not carried to the next year (no medical certificate required)</li><li>A seniority day is added every 3 years in the company</li><li>Private medical insurance</li><li>Monthly meal tickets</li><li>A work culture based on cooperation and development – customized learning paths through external providers as well as special development programs.</li><li>Wellbeing initiatives to encourage a healthy work life balance through webinars, specialized sessions and internal programs, per their colleagues’ input.</li><li>In close cooperation is a value they live by, through moments that matter, like recurring hangout parties, team buildings, team bonding events.</li></ul>

PostgreSQL DBA Engineer

As a Quality Engineer Senior Consultant, you will be a member of a QE team, responsible for executing testing activities across projects to ensure the delivery of high-quality software. You will apply your experience in manual and/or automated testing, contribute to test design, execution, and reporting, and support the team in implementing QA best practices. You will also have the opportunity to gain exposure to new automation tools and methodologies, helping drive efficiency and quality improvements in client engagements.Responsibilities: <ul><li>Execute functional and non-functional testing activities, including test design, execution, and defect management.</li><li>Support and coach junior team members by reviewing their work and sharing feedback.</li><li>Collaborate with other team members and clients to understand requirements and contribute to QA approaches.</li><li>Develop and maintain automated test scripts using available tools and frameworks.</li><li>Support the team in documenting test results, preparing reports, and sharing insights to improve testing quality.</li><li>Identify opportunities to improve QA processes and share knowledge within the team.</li><li>Promote efficient use of QA tools, frameworks, accelerators, and GenAI technologies to support test design, test data generation, defect detection, and overall testing efficiency.</li></ul>Requirements&nbsp;To qualify for the role, you must have:&nbsp;<ul><li>Bachelor’s or Master’s degree in Business Administration, Computer Science, Engineering, or a related field.</li><li>3–4 years of hands-on experience in manual and/or automated testing (ideally both).</li><li>Experience with test management and defect tracking tools.</li><li>Exposure to or interest in learning modern automation tools such as Tricentis Tosca, Katalon, or similar.</li><li>Solid understanding of QA processes, methodologies, and best practices.</li></ul><ul><li>ISTQB Foundation Level certification is considered a plus.</li><li>Ability to work collaboratively in a team environment and communicate effectively.</li><li>Excellent problem-solving skills, attention to detail, and the ability to think critically.  </li><li>Experience in Energy sector will be considered a plus.</li><li>Military obligations fulfilled where applicable.</li></ul>Benefits: <ul><li>Competitive remuneration package</li><li>Private health insurance</li><li>Ticket Restaurant card</li><li>Hybrid working model</li><li>Clear opportunities for professional growth and continuous learning</li><li>Access to modern tools, technologies, and best-practice methodologies</li></ul>

QA Engineer Senior Consultant

As a Quality Engineering Assistant Manager, you will take a hands-on approach to support a team of QE professionals, ensuring high-quality delivery across testing engagements. You will apply your strong knowledge of QA processes, test design, and execution while mentoring team members and promoting consistent best practices. You will also collaborate with clients to provide functional QA guidance and practical recommendations, while supporting managerial roles from a functional perspective to ensure smooth execution of testing initiatives. Responsibilities: <ul><li>Mentor and support the QE team in day-to-day testing activities, providing hands-on guidance in planning, test design, execution, and defect management.</li><li>Collaborate with clients to understand requirements and propose practical QA approaches to ensure quality outcomes.</li><li>Support other managerial roles by providing functional input, guidance, and assistance in implementing QA strategies, processes, and best practices across projects.</li><li>Develop and implement QA processes, methodologies, and standards to improve efficiency, consistency, and quality.</li><li>&nbsp;Monitor and ensure effective test planning, execution, defect management, and reporting.</li><li>Identify areas for improvement, drive adoption of best practices, and support the continuous development of team capabilities.</li><li>Promote efficient use of QA tools, frameworks, accelerators, and GenAI technologies to support testing activities, improve efficiency, accelerate defect detection, and enhance overall quality delivery.</li></ul>Requirements&nbsp;To qualify for the role, you must have:&nbsp;<ul><li>Bachelor’s or Master’s degree in Business Administration, Computer Science, Engineering, or a related field.</li><li>5+ years of experience in Quality Engineering, with hands-on experience in testing (manual and/or automation), or in business analysis.</li><li>Solid knowledge of QA processes, testing methodologies, and tools.</li><li>Client-facing experience, with the ability to communicate functional QA recommendations effectively.</li><li>ISTQB Foundation Level certification is considered a plus.</li><li>Experience in Energy sector will be considered a plus.&nbsp;</li><li>Excellent problem-solving skills, attention to detail, and the ability to think critically.</li><li>Strong communication and interpersonal skills, with the ability to work effectively in a collaborative team environment.</li><li>Military obligations fulfilled where applicable.</li></ul>Benefits: <ul><li>Competitive remuneration package</li><li>Private health insurance</li><li>Ticket Restaurant card</li><li>Hybrid working model</li><li>Clear opportunities for professional growth and continuous learning</li><li>Access to modern tools, technologies, and best-practice methodologies</li></ul>

QA Engineering Assistant Manager

As a Quality Engineering Manager/Senior Manager, you will be responsible for overseeing and guiding a team of 8–10 QE professionals with diverse skills and experience. You will ensure the effective delivery of high-quality testing services, including strategic oversight, governance, process standardization, and consultation to clients. You will play a critical role in driving client satisfaction, providing guidance on QA best practices, and enabling the team to deliver successful project outcomes.Responsibilities: <ul><li>Develop and implement test strategies, plans, and processes, ensuring alignment with business requirements.</li><li>Develop and implement QA strategies, processes, and governance practices, ensuring alignment with client requirements and organizational standards.</li><li>Monitor and mentor a team of Quality Engineering professionals, providing guidance and support to maximize performance and professional growth.</li><li>Collaborate with clients to understand business objectives, propose QA approaches, and provide consultation on quality-related solutions.</li><li>Manage all phases of the testing lifecycle, ensuring effective planning, execution, defect management, and reporting.</li><li>Identify areas for improvement and promote continuous enhancement of QA processes.</li><li>Promote and consult clients on QA best practices to improve overall project delivery quality and efficiency.</li><li>Support the adoption and integration of tools, frameworks, accelerators, and GenAI technologies to improve efficiency, repeatability, defect detection, and overall coverage.</li><li>Oversee project financials, including invoicing activities, ensuring alignment with contractual and organizational expectations.</li></ul>Requirements&nbsp;To qualify for the role, you must have:&nbsp; <ul><li>Bachelor’s or Master’s degree in Business Administration, Computer Science, Engineering, or a</li><li>related field.</li><li>&nbsp;8–10 years of experience in Quality Engineering, including at least 5+ years in a lead or managerial role.</li><li>Strong knowledge of QA strategy, governance, processes, and tools.</li><li>Experience in client management, including the ability to build strong relationships, manage expectations, and communicate effectively with stakeholders at all levels.</li><li>ISTQB Foundation Level certification is considered a plus.</li><li>Experience in Energy sector will be considered a plus.&nbsp;</li><li>Excellent problem-solving skills, attention to detail, and the ability to think critically.</li><li>Strong communication and interpersonal skills, with the ability to work effectively in a collaborative team environment.</li><li>Military obligations fulfilled where applicable.</li></ul>Benefits: <ul><li>Competitive remuneration package</li><li>Private health insurance</li><li>Ticket Restaurant card</li><li>Hybrid working model</li><li>Company car</li><li>Mobile phone</li><li>Clear opportunities for professional growth and continuous learning</li><li>Access to modern tools, technologies, and best-practice methodologies</li></ul>

QA Engineering Senior Manager

Our Client is expanding its AI &amp; Data division and is looking for an experienced Machine Learning Engineer&nbsp;to design, develop, and deploy advanced ML solutions that power automation and digital transformation initiatives. This role combines&nbsp;hands-on engineering&nbsp;with&nbsp;technical leadership, focusing on creating scalable, production-ready ML systems that support real-world business processes.Key Responsibilities<ul><li>Design, develop, and integrate&nbsp;machine learning models&nbsp;into production environments.</li><li>Build and maintain&nbsp;data pipelines&nbsp;and&nbsp;model training workflows&nbsp;to ensure reliable and automated processes.</li><li>Develop and enhance the company’s&nbsp;MLOps infrastructure&nbsp;for model lifecycle management, automation, and monitoring.</li><li>Write&nbsp;production-grade Python code&nbsp;and build APIs or services that expose ML models to business applications.</li><li>Continuously monitor, evaluate, and retrain models to maintain accuracy and performance.</li><li>Collaborate with&nbsp;data engineers, annotation teams, software developers, and product managers&nbsp;to align solutions with business objectives.</li><li>Participate in&nbsp;code reviews, documentation, and the definition of engineering best practices.</li></ul>Requirements<ul><li>Bachelor’s or Master’s degree in&nbsp;Computer Science, Mathematics, Statistics, or a related discipline.</li><li>4 + years&nbsp;of hands-on experience developing and deploying machine learning models.</li><li>Proven&nbsp;people management or team leadership experience.</li><li>Strong proficiency in&nbsp;Python&nbsp;and ML libraries (e.g.,&nbsp;scikit-learn, TensorFlow, PyTorch).</li><li>Solid understanding of&nbsp;MLOps tools and practices&nbsp;(e.g.,&nbsp;MLflow, Kubeflow, Airflow).</li><li>Working knowledge of&nbsp;cloud platforms&nbsp;such as AWS, GCP, or Azure.</li><li>Excellent&nbsp;analytical thinking,&nbsp;problem-solving, and&nbsp;communication skills.</li><li>Fluent in&nbsp;English, both written and spoken.</li></ul>Nice to Have<ul><li>Experience with&nbsp;document understanding,&nbsp;OCR, or&nbsp;NLP&nbsp;models.</li><li>Familiarity with&nbsp;containerization&nbsp;(Docker, Kubernetes) and CI/CD for ML pipelines.</li><li>Exposure to&nbsp;data governance,&nbsp;model monitoring, or&nbsp;AI observability&nbsp;tools.</li></ul>Why Join Them<ul><li>You’ll be part of a growing AI team within a well-established organization that is transforming its services through technology.</li><li>You’ll work on end-to-end ML systems, from data ingestion to deployment, with real business impact across automation and document intelligence domains.</li><li>If you’re passionate about building scalable ML products and want to see your models running in production, this is the right environment for you.</li></ul>&nbsp;

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