AI Lead Data Engineer

🏢 Summary: Remote AI Lead DevOps Engineer role responsible for defining and executing the MLOps and CI/CD strategy for enterprise AI platforms. The position focuses on architecting secure, compliant, and fully automated ML lifecycle governance, ensuring auditability, reproducibility, and large-scale reliability. The role combines technical leadership with hands-on design of cloud-native, DevSecOps-driven AI infrastructure. 🗂️ Requirements: 8–10 years DevOps or Cloud Engineering experience, Minimum 3 years in technical leadership or architect role, Strong knowledge of end-to-end ML lifecycle, Expertise in CI/CD pipeline design and implementation, Advanced Infrastructure as Code experience, Experience with SAST and DAST implementation, Strong IAM and access control management in cloud, Ability to design observability frameworks for ML systems, Experience with configuration management in multi-cloud environments, Knowledge of database scaling and security, Experience implementing model governance and auditability practices 📃 Skills: MLOps, CI/CD, DevSecOps, Azure, AzureDevOps, GitHubActions, Jenkins, Terraform, CloudFormation, SAST, DAST, IAM, Ansible, Puppet, MySQL, PostgreSQL, MongoDB, Observability, Git 🏢 Description: This is a remote position. We are looking for an AI Lead DevOps Engineer to spearhead the MLOps strategy for our high-impact AI accounts. With 8–10 years of experience, you will provide the technical leadership necessary to design robust, compliant, and highly automated AI platforms. You aren't just managing pipelines; you are architect the entire lifecycle governance—ensuring reproducibility, audibility, and security at an enterprise scale. Key Responsibilities: Strategic Leadership: Provide technical direction for the DevOps squad, defining the CI/CD and MLOps roadmap for the account. Model Governance & Evaluation: Implement automated model evaluation pipelines to track accuracy, precision, and recall metrics in production. Enterprise Security: Lead the DevSecOps strategy, ensuring all AI deployments comply with enterprise security standards and global data regulations. Platform Enablement: Architect self-service platforms that allow ML engineers to deploy models with minimal friction while maintaining strict governance guardrails. Auditability & Reproducibility: Ensure that every ML experiment is fully auditable through sophisticated pipeline and dataset versioning strategies. Mentorship: Mentor senior and junior engineers, driving best practices in automation, IaC, and cloud-native architecture. Requirements 8–10 years of experience in DevOps/Cloud Engineering, with at least 3 years in a technical leadership or architect-level role. Deep understanding of the end-to-end ML lifecycle (training, validation, deployment, and retraining loops). Mastery across Azure DevOps, GitHub Actions, and Jenkins. Expert-level Terraform or CloudFormation skills, including modular architecture and cross-account cloud deployments. Significant experience implementing SAST/DAST tools and managing complex IAM/Access Control frameworks in a cloud environment. Ability to design custom observability frameworks that track model drift, pipeline failures, and infrastructure ROI. Advanced knowledge of configuration management tools like Ansible or Puppet for complex multi-cloud environments. Solid understanding of database scaling and security for MySQL, PostgreSQL, and MongoDB. Understanding of how DevOps practices support responsible AI (e.g., bias tracking and audit logs). Exceptional ability to collaborate with Architects and Data Scientists to translate high-level AI needs into operational reality. Native or C1-level English, with the ability to present technical strategies to senior stakeholders. Benefits Professional training programs Work with a team that’s recognized for its excellence. We’ve been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We’ve also received the Great Place To Work® certification for five years in a row

🏢 Summary: Lead Data Engineer role focused on driving AI initiatives and building scalable cloud-based data architectures in a global environment. The position involves technical ownership of data platforms, designing secure and high-performing systems, and leading data engineering efforts in a DevOps setting. The role emphasizes AI integration, cloud infrastructure, and enterprise-grade data governance. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python in production, Strong experience designing and scaling complex data systems, Hands-on experience with AI technologies, Hands-on experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs and data integration, Experience with automation tools, Knowledge of data governance practices, Understanding of data security and compliance standards, Proven experience leading and mentoring engineers 📃 Skills: Python, SQL, AWS, Azure, Java, AI, RAG, MCP, APIs, DevOps, Automation, Monitoring, Cloud, DataEngineering, DataPipelines, Governance, Security, Compliance, Backend 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Lead Data Engineer role focused on building scalable AI and cloud-based data solutions in a global environment. The position involves leading data engineering initiatives, designing secure cloud architectures, and supporting AI applications using AWS or Azure. The offer includes hybrid work, professional development opportunities, and a comprehensive benefits package. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python, Experience designing and scaling complex data systems, Hands-on experience with AI technologies, Experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs, data integration, automation tools, and data governance, Understanding of data security and compliance standards, Leadership and mentoring experience, English and Polish proficiency (minimum B2) 📃 Skills: Python, SQL, AWS, Azure, Java, APIs, DevOps, AI, RAG, MCP, Automation, DataGovernance 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Lead Distributed Data Platform Engineer responsible for architecting and delivering enterprise-scale lakehouse and distributed data platforms to enable advanced analytics and reporting. The role combines hands-on technical leadership with team mentorship, driving scalable, secure, and high-performance data solutions in cloud-native environments. You will guide architectural decisions, enforce engineering best practices, and ensure platform reliability at scale. 🗂️ Requirements: Proven experience leading data engineering or platform teams, Strong programming skills in Python, Strong programming skills in SQL, Hands-on experience with Apache Spark in production, Experience with Delta Lake and/or Apache Iceberg in production, Experience designing distributed systems and lakehouse architectures, Experience building scalable data pipelines, Knowledge of CI/CD and automated testing practices, Experience with Kubernetes and Docker, Experience working in cloud-native environments 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD, Java, Scala, Rust 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the platform you lead will underpin how the entire organisation accesses and acts on its data. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As Lead Distributed Data Platform Engineer, you'll combine deep technical expertise with hands-on team leadership — guiding a team in designing and maintaining data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services at enterprise scale. You'll lead architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable solutions. The role emphasises technical leadership, governance best practices, and a culture of innovation and continuous improvement. You'll also participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT YOU'LL WORK ON Team leadership and mentorship Lead and mentor a team of data platform engineers, promoting collaboration, knowledge sharing, and professional growth. Set and maintain high engineering standards across the team. Distributed systems architecture Drive architectural decisions for distributed systems and lakehouse platforms using Spark, Delta Lake, and Iceberg. Facilitate architecture reviews and contribute to design decisions for fault-tolerant, future-ready systems. Data pipeline and platform delivery Oversee design and implementation of scalable data pipelines and analytics workflows, ensuring they are reliable, performant, and maintainable at scale. Engineering best practices Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all platform engineering work. Performance and cost optimisation Manage performance tuning, scalability strategies, and cost optimisation across cloud-native environments and large-scale distributed workloads. Governance and observability Champion governance, observability, and compliance frameworks across all data platforms — ensuring data remains accessible, secure, and auditable. Stakeholder communication Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure delivery aligns with business objectives and analytics needs. WHAT WE LOOK FOR Proven technical team leadership Demonstrated experience leading data engineering or platform development teams — mentoring engineers, owning architectural decisions, and driving delivery outcomes. Python and SQL Strong programming skills in both Python and SQL applied to production data platform work at scale. Apache Spark Hands-on experience with Spark for distributed data processing, including performance tuning and optimisation in production environments. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You understand the trade-offs and have applied these technologies in production at scale. Analytics tooling Familiarity with dbt, Databricks, and Snowflake for analytics workflows and large-scale data processing. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data platform systems. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Communication and stakeholder management Strong communication skills with the confidence to operate across engineering teams, cross-functional partners, and senior leadership. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. Exposure to service mesh and advanced orchestration patterns. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 270,000 – 406,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Lead .NET Engineer role combining hands-on backend development with technical leadership, owning architecture, core platform services, APIs, and payment integrations in a distributed AWS environment. The position includes defining technical direction, mentoring engineers, driving CI/CD and operational excellence, and promoting AI-assisted development practices. After a short onboarding period in the US, the role is fully remote with long-term engagement in a strategic product initiative. 🗂️ Requirements: 6–10+ years of experience building and operating production software systems, Experience in Technical Lead or Lead Engineer role, Strong backend development experience with C# and .NET, Experience designing and operating distributed systems and microservices, Strong SQL and database design skills, Hands-on experience with AWS (SQS, DynamoDB, S3, ECS, Lambda), Experience owning and improving CI/CD pipelines, Experience in payments, financial services, or regulated environments, Working knowledge of React or Vue 📃 Skills: C#, .NET, AWS, ECS, Lambda, SQS, DynamoDB, S3, SQL, Microservices, REST, CI/CD, React, Vue, AI 🏢 Description: Lead .NET Engineer Remote 140–160 PLN/h B2B Full-time (FTE) *Project starts with a 2–3 week onboarding and training period in the US, followed by fully remote work. About the role We are looking for an experienced Lead .NET Engineer to take ownership of a squad responsible for core platform services, APIs, and payment integrations. In this role, you will combine hands-on software engineering with technical leadership. You will define technical direction, partner with Product on roadmap delivery, mentor engineers, and help drive the adoption of AI-assisted development practices across the software delivery lifecycle. Responsibilities Own squad-level architecture and technical decision-making. Lead the design, development, and operation of backend services and APIs. Ensure high standards of code quality, performance, security, and reliability. Drive incident management and operational excellence. Collaborate closely with Product Managers and stakeholders to deliver roadmap priorities. Mentor engineers through coaching, technical guidance, and regular feedback. Participate in hiring and team growth activities. Promote and implement AI-assisted development tools and best practices. Contribute to continuous improvement of engineering processes, CI/CD, and platform capabilities. Must-have requirements 6–10+ years of experience building and operating production software systems. Proven experience in a Technical Lead, Lead Engineer, or similar leadership role. Strong backend development experience with C#/.NET. Working knowledge of frontend technologies such as React or Vue. Experience designing and operating distributed systems and microservice architectures. Strong SQL and database design skills. Experience working within payments, financial services, or other regulated environments. Hands-on experience with AWS services, including: SQS DynamoDB S3 ECS Lambda Experience owning and improving CI/CD pipelines. Strong communication and stakeholder management skills. Nice to have Experience building large-scale payment platforms or fintech products. Previous people-management responsibilities. Experience with platform modernization and cloud transformation initiatives. Experience implementing AI-powered engineering tools and workflows. Tech Stack C# .NET AWS ECS Lambda SQS DynamoDB S3 SQL Microservices REST APIs CI/CD React / Vue AI-assisted Development What we offer Long-term engagement in a strategic product initiative. High-impact technical leadership role. Opportunity to shape engineering standards and architecture. Exposure to modern AI-assisted development practices. International environment and collaboration with US-based teams. Fully remote work after onboarding period in the US.

🏢 Summary: Leadership role responsible for guiding AI Engineers and driving AI technology direction, with strong involvement in hands-on project delivery, R&D, and presales activities. The position focuses on developing and implementing AI solutions, especially in the LLM or ML domain, while ensuring high architectural and quality standards. It combines technical leadership with active participation in client discovery and solution design. 🗂️ Requirements: Proven experience in LLM or ML domain, Hands-on experience with large language models, Knowledge of prompt engineering, RAG, fine-tuning, embeddings, vector databases, Experience with LangChain or Semantic Kernel or HuggingFace, Experience with Azure OpenAI or Azure AI Foundry or Azure Machine Learning or similar platforms, Practical knowledge of scikit-learn or TensorFlow or PyTorch, Experience with ML lifecycle management tools, Proficiency in Python, Experience leading technical teams 📃 Skills: Python, LLM, RAG, Embeddings, LangChain, SemanticKernel, HuggingFace, AzureOpenAI, AzureAIFoundry, AzureML, scikit-learn, TensorFlow, PyTorch, MLflow 🏢 Description: Twoja rola: Jako AI Lead będziesz liderem zespołu AI Engineerów. To stanowisko łączy elementy technologicznego przywództwa, wsparcia w procesie sprzedaży, pracy z klientami oraz rozwoju kompetencji wewnątrz zespołu AI. Będziesz odpowiedzialny/a za: Rozwój zespołu Mentoring i wsparcie w rozwoju kompetencji technicznych i miękkich członków zespołu. Inspirowanie do innowacji, eksperymentowania i poszukiwania nowych rozwiązań. Identyfikowanie obszarów wymagających wzmocnienia kompetencji oraz planowanie ich uzupełnienia. Technologiczne przywództwo Wyznaczanie kierunku rozwoju technologii AI w Onex Group zgodnie z najnowszymi trendami i strategią firmy. Dbanie o jakość, architekturę i dobre praktyki w projektach. Przede wszystkim udział w projektach i realizacji zadań projektowych Tworzenie koncepcji, prototypów i PoC w ramach działań R&D. Wsparcie w procesie sprzedaży Prowadzenie procesów discovery i warsztatów z klientami Udział w procesach presales i przygotowywanie koncepcji rozwiązań. Tworzenie technicznego wkładu do ofert i wsparcie przy wycenach. Czego oczekujemy? Doświadczenie i wiedza techniczna Od kandydata oczekujemy znajomości oraz posiadanie kompetencji w jednym z wymienionych obszarów technologicznych (preferowany obszar LLM): Znajomość oraz doświadczenie w obszarze dużych modeli językowych (LLM): Znajomość koncepcji: prompt engineering, RAG, fine-tuning, embeddings, bazy wektorowe. Doświadczenie z narzędziami: LangChain lub Semantic Kernel, HuggingFace. Azure OpenAI, Azure AI Foundry, Azure Machine Learning lub podobne Znajomość oraz doświadczenie obszarze uczenia maszynowego (ML): Frameworki i ekosystem ML: praktyczna znajomość scikit-learn, TensorFlow lub PyTorch oraz narzędzi do zarządzania cyklem życia modeli, takich jak MLflow Znajomość języków programowania: Python, Umiejętności przywódcze / miękkie Doświadczenie w prowadzeniu zespołu. Przywództwo oparte na mentoringu, dobrej komunikacji i motywowaniu. Umiejętność w zakresie biegłości operacyjnej w projektach, zarządzania priorytetami i rozwiązywania konfliktów. Umiejętności biznesowe (mile widziane) Doświadczenie w pracy z klientem i tłumaczeniu zagadnień technicznych na język biznesowy. Prowadzenie discovery u klientów i umiejętność inspirowania ich możliwościami AI. Współpraca ze sprzedażą oraz przygotowywanie wraz z nią ofert i estymacji. Co oferujemy? Swobodę w działaniu oraz decyzyjność Kulturę organizacyjną opartą na odpowiedzialności, zaufaniu i realizacji założonych celów Elastyczne godziny pracy, możliwość częściowej pracy zdalnej Opiekę medyczną, Kartę Multisport, Ubezpieczenie na Życie, naukę języka angielskiego Integracyjne wyjazdy i eventy – świetna atmosfera to podstawa!

🏢 Summary: The role involves leading and executing digital transformation initiatives with a strong focus on AI-driven automation and data analytics to enhance operational efficiency and business growth. The position requires aligning digital strategy with business goals, overseeing multiple projects, and ensuring successful adoption of innovative technologies. The candidate will drive AI integration, automation strategies, and data-informed decision-making across the organization. 🗂️ Requirements: Bachelor’s degree in Computer Science, Business, Engineering or related field, Minimum 7 years of experience leading complex digital transformation projects, Proven experience with AI-driven automation and Generative AI, Strong data analytics and complex data interpretation skills, Deep understanding of digital technologies and SaaS platforms, Experience in leading cross-functional technical teams, Product management experience delivering measurable value, Knowledge of change management principles 📃 Skills: AI, GenerativeAI, Automation, DataAnalytics, SaaS, DigitalTransformation, ProductManagement, Agile, ProjectManagement, DataAnalysis 🏢 Description: Introduction & Summary The Digital Transformation Team Lead will be responsible for spearheading the implementation of innovative digital strategies to enhance operational efficiency and drive business growth through AI integration. The ideal candidate will possess extensive expertise in AI-driven transformation, automation strategy, and data analytics, ensuring effective alignment of solutions with business objectives. Main Responsibilities Lead the organization’s digital strategy, ensuring alignment with business goals and managing multiple projects simultaneously. Oversee the execution of digital transformation initiatives, providing direction and leadership. Facilitate the delivery of impactful digital solutions, ensuring clarity on problem definition and stakeholder alignment. Enhance customer journeys by leveraging AI technologies to improve both customer and employee experiences. Utilize data-driven insights to inform decision-making and foster a culture of data analytics. Drive operational execution, ensuring initiatives are delivered on time, within scope, and with measurable impact. Engage with stakeholders for support on digital transformation initiatives, ensuring transparent communication. Manage change effectively to facilitate the smooth adoption of digital solutions. Build cross-functional teams and foster a culture of innovation and collaboration. Mitigate risks associated with digital initiatives, ensuring project quality standards are met. Continuously evaluate emerging technologies to maintain a competitive edge. Key Requirements Bachelor's degree in a relevant field (e.g., Computer Science, Business, Engineering); a master's degree or relevant certifications are preferred. Minimum of 7 years of experience in leading complex digital transformation projects. Proven experience with AI-driven automation, including Generative AI. Strong analytical skills to interpret complex data and make informed decisions. Deep understanding of digital technologies and SaaS platforms. Demonstrated leadership in mentoring and building high-performing teams. Excellent product management capabilities to drive measurable value. Outstanding communication and negotiation skills. Proficiency in change management principles. Relevant certifications in project management or digital transformation are a plus. Nice to Have Experience in AI technologies and their strategic application in business. Knowledge of agile methodologies and principles. Strong stakeholder engagement experience in technical fields.

🏢 Summary: Lead AI Software Developer role focused on architecting and scaling AI-powered applications, backend systems, and multi-agent workflows across cloud and enterprise environments. The position involves designing secure integrations, optimizing LLM-based solutions, and leading technical delivery and best practices. It combines hands-on AI development with backend architecture and technical leadership. 🗂️ Requirements: Degree in Computer Science, AI, Data Science or related field, 8+ years of software engineering experience, 5+ years of Python backend development in production, Experience building and scaling Python applications, Hands-on experience with AI Agents, RAG and MCP, Experience with AWS or Azure cloud platforms, Experience with storage systems and databases, Knowledge of containerization and Kubernetes, Experience with API integrations and enterprise system connectivity, Leadership and mentoring experience 📃 Skills: Python, AWS, Azure, Kubernetes, RAG, MCP, APIs, Cloud, Databases, Containerization, AI, LLM 🏢 Description: We are seeking an experienced Lead AI Software Developer to design and scale AI-powered applications and integrations. In this role, you will architect backend systems, lead AI agent development, and ensure secure, scalable integration across cloud platforms and enterprise systems. Key Responsibilities Design and maintain middleware, APIs, and connectors integrating AI agents with enterprise systems Architect scalable backend services and cloud-based solutions (AWS/Azure) Develop and optimize multi-agent workflows and adaptive decision logic Fine-tune prompts and LLM-based solutions for domain-specific use cases Lead code reviews, mentor developers, and define development best practices Drive complex API integrations with internal and external AI platforms (incl. MCP servers) Remove technical roadblocks and ensure timely delivery Collaborate with AI, Data, and Platform teams to optimize automation architectures Maintain technical documentation and promote continuous improvement Requirements Degree in Computer Science, AI, Data Science, or similar field 8+ years of software engineering experience, including 5+ years of Python backend development (production) Strong experience building and scaling Python applications Hands-on experience with AI technologies (AI Agents, RAG, MCP) Experience with cloud platforms (AWS or Azure), storage, databases, and AI services Knowledge of containerization and Kubernetes Experience with API integrations and enterprise system connectivity Strong leadership and mentoring experience Excellent communication skills; fluent in Polish and English (min. B2); German is a plus Willingness to travel internationally (~10%) Nice to have: Experience with LangChain, LangGraph, multi-agent systems, prompt engineering, and LLM fine-tuning. What We Offer Work in a global and innovative technology environment Direct impact on enterprise AI and automation solutions Professional development and access to training programs Hybrid work model with flexible hours (central Wroclaw office) Competitive benefits package, cafeteria system, CSR initiatives, and employee clubs

🏢 Summary: Lead Data Engineer role focused on driving architecture and leading a team to build scalable, secure ETL/ELT pipelines and analytics-ready data models on modern cloud platforms. The position combines hands-on engineering with technical leadership, ensuring high standards in governance, observability, and performance optimisation. You will shape data infrastructure that supports large-scale analytics across the organisation. 🗂️ Requirements: Proven experience leading data engineering or analytics engineering teams, Strong programming skills in SQL, Strong programming skills in Python, Hands-on experience with Airflow or Prefect in production, Deep practical experience with dbt, Experience with Snowflake or Databricks at scale, Strong knowledge of dimensional modelling and SCD strategies, Experience implementing data quality and governance frameworks, Experience with CI/CD and automated testing in data systems 📃 Skills: SQL, Python, Airflow, Prefect, dbt, Snowflake, Databricks, ETL, ELT, CI/CD, SCD, Dimensional, Git, IaC 🏢 Description: ABOUT THE COMPANY Our client is a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the infrastructure you lead will have real consequence across the organisation. ABOUT THE ROLE We're looking for a Lead Data Engineer to combine deep technical expertise with hands-on team leadership, guiding a team of data engineers building and maintaining ETL/ELT pipelines, data models, and governance frameworks that power analytics and reporting across the organisation. This is a technical leadership role — you'll drive architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable data solutions. You'll collaborate closely with stakeholders to align technical work with business objectives, champion governance and observability standards, and foster a culture of continuous improvement. The expectation is that you're equally effective in an architecture review as you are pairing with an engineer on a tricky pipeline problem. WHAT YOU'LL WORK ON Team leadership and mentorship Lead and mentor a team of data engineers, promoting collaboration, knowledge sharing, and professional growth. Set the standard for engineering quality and hold the bar consistently. Architecture and pipeline design Drive architectural decisions for ETL/ELT pipelines, orchestration frameworks (Airflow/Prefect), and transformation layers (dbt). Facilitate architecture reviews and contribute to design decisions for scalable, fault-tolerant systems. Analytics data modelling Oversee design and implementation of analytics-ready data models — dimensional schemas, SCD strategies, and semantic layers — that internal teams can build on reliably. Engineering best practices Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work. Platform optimisation Manage performance tuning and cost optimisation for Snowflake, Databricks, and related cloud data platforms at scale. Governance and observability Champion governance, observability, and compliance frameworks across all data workflows — including data quality, lineage tracking, and multi-tenant environment controls. Stakeholder communication Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure timely delivery aligned with business objectives. WHAT WE LOOK FOR Proven technical team leadership Demonstrated experience leading data engineering or analytics-focused development teams — mentoring engineers, driving architectural decisions, and owning delivery outcomes. SQL and Python Strong programming skills in both SQL and Python, applied to production data systems at scale. ETL/ELT orchestration Hands-on experience with orchestration tools — Airflow and/or Prefect — in production pipeline environments. dbt expertise Deep practical experience with dbt for transformation workflows and analytics modelling, including testing, documentation, and modular project design. Snowflake and Databricks Familiarity with Snowflake and/or Databricks for large-scale data processing, including performance tuning and cost management. Data modelling principles Solid understanding of data modelling principles, incremental strategies, and schema design for analytics — dimensional modelling, SCDs, and semantic layer design. Governance and data quality Knowledge of data quality frameworks, lineage tracking, and governance in multi-tenant environments. Software engineering practices Familiarity with CI/CD, automated testing, and infrastructure-as-code practices applied to data systems. Communication and stakeholder management Strong communication skills with the ability to operate confidently across technical teams and business stakeholders. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 270,000 – 406,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements, hybrid model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Leadership role focused on building and managing an AI & Data practice, driving client engagement, technical strategy, and delivery across AI, machine learning, data engineering, and cloud platforms. The position combines practice leadership, pre-sales support, team development, and hands-on technical oversight for scalable AI and data solutions. The role is on-site in Greensboro, NC, Broomfield, CO, or Troy, MI with competitive salary and performance bonus. 🗂️ Requirements: 12-15 years in consulting, engineering services, or technology-driven organizations, 5+ years in AI, Data, or Analytics leadership roles, Experience building and scaling technical teams or practices, Knowledge of Generative AI technologies and LLM ecosystems, Experience with AI/ML frameworks, Experience with data engineering platforms and distributed systems, Experience with cloud AI ecosystems, Experience with MLOps or LLMOps tools, Understanding of data governance, security, and AI regulations, Bachelor's degree in Computer Science, Data Science, AI, or related field 📃 Skills: Python, TensorFlow, PyTorch, Scikit-learn, Spark, Databricks, AWS, Azure, GCP, SageMaker, Bedrock, Vertex, MLflow, Kubeflow, ETL, ELT, RAG, LLMOps, MLOps, AI, MachineLearning, DeepLearning, DataEngineering, PromptEngineering, Containerization, Orchestration 🏢 Description: Responsibilities Practice Leadership & Management Lead and manage the AI & Data practice. Manage and steer the allocation of practice resources across multiple activities, including: - Technical pre-sales support - Technical expertise delivery to projects - Recruitment support - Training and competency development Provide line management and leadership to members of the practice including technical leadership across AI and Data. Define skills development objectives for practice members and evaluate progress and effectiveness. Develop, improve, and standardize processes, methodologies, and tools. Foster a culture of collaboration, innovation, and knowledge sharing across the practice. Client Engagement & Pre-Sales Partner with Sales and Account teams to identify and shape AI & Data opportunities. Lead or contribute to solutioning, proposals, and RFP responses. Act as a trusted advisor in client discussions and executive forums. Align AI & Data solutions with business value and client outcomes. Technical Leadership & Innovation Provide leadership across advanced AI & Data domains: - Generative AI & LLM ecosystems (prompt engineering, RAG, multi-agent systems) - Data Engineering & Modern Data Platforms (ETL/ELT, streaming, data lakes, data mesh) - Cloud-based AI architectures (AWS, Azure, GCP AI services) - Machine Learning & Deep Learning (supervised, unsupervised, reinforcement learning) Support delivery teams with hands-on guidance and expert oversight. Drive development of AI & Data offerings, accelerators, and reusable assets. Identify opportunities for AI-driven productivity gains and automation. Ensure adoption of industry best practices and scalable architectures. Qualifications - 12-15 years of experience in consulting, engineering services, or technology-driven organizations - 5+ years of experience in AI, Data, or Analytics leadership roles - Proven experience building and scaling technical teams or practices - Experience in Generative AI technologies (LLMs, RAG pipelines, prompt engineering, API-based AI services) - Experience with AI/ML frameworks (Python ecosystem, TensorFlow, PyTorch, Scikit-learn) - Experience with Data Engineering tools & platforms (Spark, Databricks, distributed systems) - Experience with Cloud AI ecosystems (Azure AI, AWS SageMaker/Bedrock, Google Vertex AI) - Experience with MLOps / LLMOps tools (MLflow, Kubeflow, containerization, orchestration) - Understanding of data governance, security, and AI regulations Skills & Competency Management - Create, maintain, and manage the practice skill matrix - Identify competency gaps and develop capability-building plans - Develop and coordinate technical training programs and certification initiatives - Build and strengthen a team of experts through recruitment, coaching and mentoring, internal talent development and training - Support career development planning and succession management within the practice - Promote technical communities, best practices, and continuous learning initiatives Educational Qualifications - Bachelor's degree (or higher) in Computer Science, Data Science, AI, or related field - Certifications in AI/ML, Cloud are a plus Salary Range: $160,000-$190,000 + Annual Performance Bonus Note: This position is on-site and can be located in Greensboro, NC, Broomfield, CO, or Troy, MI. Drug Screening Requirement: Candidates selected for employment will be required to successfully complete a pre-employment drug screening as a condition of hire.