Lead Cloud Platform Engineer (Azure, Databricks & DevSecOps)

🏢 Summary: Remote Platform Engineer role focused on designing, building, and operating enterprise-grade Azure data platforms for BI and analytics teams. The position centers on Infrastructure as Code, CI/CD automation, Databricks platform management, and secure cloud architecture. The engineer acts as a platform advisor, ensuring reliability, security, and scalability of Azure-based data solutions. 🗂️ Requirements: Strong admin-level experience with Microsoft Azure, Experience with Entra ID / Azure AD and RBAC, Hands-on experience with Azure networking, ADLS Gen2, Key Vault, Commercial experience with Terraform in modular, multi-environment setups, Hands-on CI/CD using Azure DevOps, GitHub Actions or GitLab, Practical platform experience with Databricks (clusters, jobs, governance), Platform/SRE mindset with monitoring and incident management, Scripting skills in PowerShell or Python, Experience with enterprise cloud architectures, English and Polish proficiency, Power BI experience 📃 Skills: Azure, EntraID, AzureAD, RBAC, Networking, ADLSGen2, KeyVault, Terraform, CICD, AzureDevOps, GitHubActions, GitLab, Databricks, AzureMonitor, LogAnalytics, PowerShell, Python, PowerBI 🏢 Description: In Cyclad we work with top international IT companies in order to boost their potential in delivering outstanding, cutting-edge technologies that shape the world of the future. We are seeking an experienced Platform Engineer to join our client, an IT company specializing in AI consultancy. You will have a key role in designing, building, and operating enterprise-grade data platforms that enable analytics teams to deliver real business value. You will be responsible for the Azure foundation behind Business Intelligence and Data solutions — from secure networking and identity, through Infrastructure as Code, to Databricks operations and CI/CD automation. This role is ideal for someone with a strong platform/SRE mindset who enjoys building scalable cloud architectures, automating everything, and acting as a technical advisor for analytics and BI teams. Project information: Work Setup: 100% Remote work Rate: 160 – 180 PLN/net/h + VAT (B2B contract) Start date: March 2026/ depending on candidate availability Language: English (min B2+) Project scope: Design and operate enterprise Azure data platforms (identity, networking, storage, security). Build Infrastructure as Code with Terraform (modules, environments, Azure + Databricks providers). Create and maintain CI/CD pipelines (Azure DevOps / GitHub Actions / GitLab). Manage Databricks from the platform side (clusters, jobs, secrets, repos, permissions). Implement monitoring and observability (Azure Monitor / Log Analytics). Support analytics teams by ensuring stability, performance, and security. Troubleshoot production issues and drive RCA. Automate operations using PowerShell and/or Python. Act as a platform advisor for BI and data teams. Requirements: Strong admin-level experience with Microsoft Azure (Entra ID / Azure AD, RBAC, networking, ADLS Gen2, Key Vault). Commercial experience with Terraform (modular, multi-env setups). Hands-on CI/CD using Azure DevOps, GitHub Actions or GitLab. Practical platform knowledge of Databricks (clusters, jobs, governance). Platform/SRE mindset (monitoring, incidents, reliability). Scripting skills (PowerShell/Python). Experience with enterprise cloud architectures. English & Polish proficiency. Power BI background We offer: Full-time job agreement based on B2B Private medical care with dental care (covering 70% of costs) + rehabilitation package. Family package option possible Multisport card (also for an accompanying person) Life insurance

🏢 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: 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: Remote Full Stack Developer role focused on architecting, building, and deploying a multi-tenant analytics dashboard platform that delivers large-scale consumer intelligence insights. The position involves end-to-end ownership of frontend, backend, security, and cloud infrastructure, with strong emphasis on React, Python/FastAPI, and Azure-based DevOps. You will lead technical decisions and implement scalable, secure, production-grade solutions. 🗂️ Requirements: 7–10+ years full stack development experience, 5+ years backend development with Python and FastAPI in production, Experience with ASP.NET Core and C#, 4+ years building production applications with React and TypeScript, Minimum 2+ years production experience with Auth0 (SSO, RBAC, MFA), Minimum 2+ years experience deploying applications on Kubernetes/AKS, Production experience with Azure Key Vault integration, Minimum 2+ years building CI/CD pipelines in Azure DevOps, Strong SQL skills with SQL Server and/or PostgreSQL, Proficiency in Docker containerization for frontend and backend applications 📃 Skills: Python, FastAPI, C#, .NET, ASP.NET, React, TypeScript, Auth0, Kubernetes, AKS, Azure, AzureDevOps, AzureKeyVault, Docker, SQL, SQLServer, PostgreSQL, Databricks, Redis, Celery, Terraform, ARM, Helm, TailwindCSS, Superset, Recharts, D3.js, Chart.js, ECharts, Redux, Zustand, ReactQuery, JWT, Pydantic, SQLAlchemy, EntityFramework, Dapper, xUnit, Moq, Jest, Cypress, OpenAPI, Swagger 🏢 Description: A rapidly-growing AI Consumer Intelligence Platform is hiring a remote Full Stack Developer Our platform synthesizes massive-scale data (billions of Google searches, social conversations, product reviews, and videos) to deliver actionable consumer insights for clients such as Coca-Cola, Unilever, and Bayer. We are hiring a Full Stack Developer to lead the technical implementation of this dashboard platform. You will work to architect, build, and deploy the application, making key technical decisions and establishing patterns that the broader team will follow. Role Overview This role requires someone who can work independently with minimal oversight, has deep expertise in React, Python/FastAPI, and .NET and has hands-on production experience with Auth0, Kubernetes, Azure Key Vault, and Azure DevOps. You should be comfortable owning the full stack from database queries to UI polish. You are obsessed with building dashboards that help users quickly reach the "aha" moment, the insight that changes their business. You understand that great analytics tools require both powerful backends and intuitive, fast front-ends. Key Responsibilities Architecture & Technical Leadership • Architect the end-to-end solution, including frontend component structure, API design, data access patterns, and deployment topology. • Make technical decisions on frameworks, libraries, and patterns; document architectural decisions for the team. • Design a multi-tenant architecture supporting customer-specific configurations, including product line and country segments. • Establish coding standards, review processes, and best practices for the project. Backend Development - Python/API (Primary), .NET (Secondary) • Build high-performance RESTful APIs using Python and FastAPI as the primary backend framework to serve analytics data to the React frontend. • Support and maintain secondary backend services using .NET / ASP . net Core where appropriate. - Implement efficient data access layers connecting to Databricks (via API's), SQL Server, and PostgreSQL. • Design and implement caching strategies using Redis and in-memory caching to optimize response times for data-heavy queries. • Build background services for report generation, data refresh, and scheduled tasks using Python workers, task queues, scheduled jobs, or .NET hosted services where applicable. • Implement comprehensive logging, health checks, and observability using Azure Monitor and Application Insights. Frontend Development - React • Build a modern, responsive React application with TypeScript, implementing interactive dashboards and data visualizations. • Develop reusable component library with consistent styling using TailwindCSS or styled-components. • Implement complex data visualizations using Superset or other charting libraries such as Recharts, Chart.js, D3.js, or Apache ECharts. • Optimize frontend performance for large datasets including virtualization, lazy loading, and efficient state management. • Integrate Auth0 SDK for frontend authentication flows, token management, and protected routes. Authentication, Authorization & Security • Utilize end-to-end authentication using Auth0, including SSO, MFA, and social login configurations. • Design and implement role-based access control using Auth0 roles and permissions mapped to application features. • Integrate Azure Key Vault for secure storage and retrieval of secrets, API keys, connection strings, and certificates. • Implement secure API authentication using JWT tokens with proper validation and refresh mechanisms. • Ensure compliance with security best practices, including OWASP guidelines, data encryption, and audit logging. DevOps, Infrastructure & Deployment • Work with DevOps to design and implement Kubernetes deployments on Azure Kubernetes Service, including pod configurations, services, ingress, and horizontal pod autoscaling. • Work with DevOps to build comprehensive CI/CD pipelines for automated build, test, and deployment across dev, staging, and production environments. • Create and maintain Docker containers for both frontend and backend applications with optimized, multi-stage builds. • Work with DevOps to implement infrastructure as code using Terraform or ARM templates for reproducible deployments. • Configure environment-specific settings, feature flags, and deployment slots for zero-downtime releases. • Set up monitoring, alerting, and dashboards using Azure Monitor, Application Insights, and Log Analytics. Required Qualifications - 7-10+ years in full stack development - Python/FastAPI : 5+ years of backend development with Python, including production experience building APIs with FastAPI - .NET / C# : Experience with ASP .net Core, Entity Framework, and Web APIs. Secondary backend experience preferred. - React / TypeScript : 4+ years building production React applications - Auth0 : 2+ years implementing Auth0 in production, including SSO, RBAC, and MFA - Kubernetes : 2+ years deploying and managing apps on Kubernetes/AKS - Azure Key Vault : Production experience integrating Key Vault for secrets management - Azure DevOps : 2+ years building CI/CD pipelines in Azure DevOps - Databases : Strong SQL skills with SQL Server and/or PostgreSQL - Docker : Proficient in containerizing Python/FastAPI, .NET, and React applications Technical Skills Backend - Python / FastAPI • Python backend development with FastAPI • RESTful API design and implementation • Pydantic models and validation • Dependency injection and middleware patterns in FastAPI • Async programming and performance optimization • SQLAlchemy, SQLModel, or equivalent ORM/data access libraries • Integration with SQL Server, PostgreSQL, and Databricks APIs • Background jobs using Celery, Redis Queue, APScheduler, Azure Functions, or similar tools • API documentation using OpenAPI/Swagger • Unit and integration testing with pytest or similar frameworks Secondary Backend - .NET Core • ASP.NET Core Web APIs with dependency injection, middleware, and filters • Entity Framework Core and/or Dapper for data access • Background services using IHostedService or Hangfire • API documentation with OpenAPI/Swagger • Unit testing with xUnit, Moq, and integration testing patterns Frontend (React) • React 18+ with hooks, context, and functional components • TypeScript for type-safe development • State management with Redux Toolkit, Zustand, or React Query • Data visualization libraries, including Superset or other options such as Recharts, Chart.js, D3.js, or ECharts • CSS frameworks, preferably TailwindCSS, or CSS-in-JS solutions • Testing with Jest, React Testing Library, and Cypress Auth0 Expertise • Auth0 tenant configuration and application setup • Universal Login customization and branding • Auth0 Rules, Actions, and Hooks for custom logic • Role-Based Access Control implementation • Machine-to-machine authentication for backend services • Auth0 SDK integration with Python/FastAPI, .NET, and React Kubernetes & Azure • Kubernetes concepts: Deployments, Services, ConfigMaps, Secrets, Ingress • Azure Kubernetes Service provisioning and management • Helm charts for application packaging • Azure Key Vault integration with AKS using CSI driver or pod identity • Azure DevOps YAML pipelines for build and release • Infrastructure as Code using Terraform or ARM templates) Preferred Qualifications • Experience with Databricks or Spark for big data integration • Experience integrating LLM/GenAI services, including OpenAI or Azure OpenAI, into applications • Power BI embedded analytics or Apache Superset experience • GraphQL experience, both server and client • Background in consumer insights, CPG, or market research data domains • Experience building multi-tenant SaaS applications • Azure certifications such as AZ-204, AZ-400, or AKS specialty

🏢 Summary: Design and scale high-throughput data pipelines on cloud platforms to support advanced analytics and AI-driven products. The role focuses on building distributed data architectures in AWS and Databricks, ensuring performance, governance, and data quality. You will collaborate with AI/ML teams to deliver scalable, production-grade data solutions. 🗂️ Requirements: 3+ years of data engineering experience, Strong Python programming skills, Experience with Spark or Scala, Experience building distributed data pipelines in cloud environments, Knowledge of data modeling and data warehousing principles, Bachelor’s or Master’s degree in Computer Science or Engineering 📃 Skills: Python, Spark, Scala, AWS, Glue, EMR, Fargate, StepFunctions, Databricks, SQL, APIs, GenAI, GraphDB 🏢 Description: Data Engineer – Cloud & AI Platforms We’re looking for a Data Engineer to design and scale high-throughput data pipelines supporting advanced analytics and AI-driven products. What You’ll Do Architect and maintain distributed data pipelines in Databricks and AWS (Glue, EMR, Fargate, Step Functions) Ingest and process large volumes of structured and unstructured data (internal, market, third-party, alternative sources) Collaborate with AI/ML and engineering teams to design scalable data architectures and APIs Optimize performance and cost using Spark and cloud-native best practices Implement data governance, privacy, lineage, and access controls Build automated validation, monitoring, and data quality frameworks Evaluate emerging GenAI and data tooling to enhance platform capabilities What You Bring 3+ years of experience in data engineering Strong Python and experience with Spark or Scala Proven experience building distributed pipelines in cloud environments Solid understanding of data modeling, architecture, and warehousing principles Innovative problem-solving mindset Bachelor’s or Master’s degree in Computer Science or Engineering Nice to have: Experience with graph databases.

🏢 Summary: Cloud Platform Engineer role focused on designing, building, operating, and maintaining Azure-based cloud infrastructure across multiple subscriptions and global applications. The position combines infrastructure engineering and operations, including Terraform-based deployments, AKS management, and incident handling. It requires close collaboration with technical teams to deliver secure, scalable, and reliable Azure environments. 🗂️ Requirements: 3+ years experience with Azure core services (Resource Manager, VMs, Scale Sets, Storage, Networking), 3+ years experience with Azure Kubernetes Service, 2+ years experience with Terraform, 3+ years experience in Windows or Linux administration, Experience troubleshooting IaaS and PaaS environments, Ability to manage incidents and meet SLA targets 📃 Skills: Azure, ARM, VMs, ScaleSets, Blob, VNets, NSG, LoadBalancer, AppGateway, DNS, PrivateLink, AKS, Terraform, Windows, Linux, IaaS, PaaS 🏢 Description: ☁️ Azure Cloud Platform Engineer We are looking for a talented and experienced Cloud Engineer to join our growing team. As well as experience with cloud infrastructure, networking, and security, the Cloud Platform Engineer will be responsible for operating, monitoring, and maintaining our many Azure subscriptions and associated global applications. This is a cloud infrastructure role. As a Cloud Platform Engineer with cloud architecture, you will work closely with other data professionals, software engineers, and business stakeholders to build, maintain and support[CU1] [MU2] efficient, scalable, and secure data pipelines. This role involves both engineering and operations, requiring comfort with project work and handling incident tickets as part of the team. Work mode: Hybrid — Prague, Czech Republic (2–3 days in the office) or Bucharest, Romania Type of contract: B2B contract Responsibilities: Design, build and maintain Azure based infrastructure with Terraform modules (IaaS and PaaS resources) as part of new projects or updates needed to production environments Troubleshoot IaaS and PaaS issues raised via SNow incident and meet ticket closure SLA’s Documentation and knowledge sharing: create and maintain environment diagrams, playbooks, runbooks, and best practice documents Communicate with internal business partners including guidance on application design Qualifications: MUST 3+ years of experience with Azure core services: Resource Manager, Virtual Machines/Scale Sets, Storage (Blob/Files), Networking (VNets, NSGs, Load Balancer, App Gateway, DNS, Private Link) 3+ year of experience in Windows or Linux administration, with strong problem-solving abilities 3+ years of experience with Azure Kubernetes Service 2+ years of experience with Terraform Ability to work independently and initiate tasks without supervision and utilize strong interpersonal and organizational skills, including the ability to meet deadlines, work in a team environment, follow written policies and procedures and always maintain superior customer service Excellent problem-solving and analytical skills NICE TO HAVE [MU3] [J(4] Experience with BICEP and/or ARM templates CI/CD and automation: Azure DevOps Pipelines or GitHub Actions (YAML) Familiarity with configuration management tools, preferably Ansible Familiarity with configuring and managing Kafka/MongoDB/Elasticsearch Competency in scripting languages such as Bash, Shell, or PowerShell Strong communication and teamwork skills Benefits: Collaborative and supportive team culture Opportunity to work with global teams and stakeholders Exposure to innovative and impactful projects 📩 If you’re interested and meet the qualifications, please send your CV to Alina Pchelnikova at alina.pchelnikova@dcvtechnologies.co.uk

🏢 Summary: 12+ month B2B contract for a remote Platform Engineer to design and operate a Kubernetes-based internal cloud platform enabling reliable deployments for application and data teams. The role focuses on building self-service CI/CD capabilities, ensuring platform reliability, security, and observability, and supporting multi-environment, primarily Azure-based, deployments. 🗂️ Requirements: Strong expertise in Kubernetes (AKS and on-prem), Hands-on experience with CI/CD pipelines, Proficiency in Azure DevOps YAML, Solid understanding of platform reliability, observability, and security, Operational experience in multi-cloud environments, Experience working with Microsoft Azure 📃 Skills: Kubernetes, AKS, Azure, AzureDevOps, YAML, CICD, Observability, Security, Multicloud 🏢 Description: Summary: The Platform Engineer role focuses on building and operating a shared cloud platform to facilitate reliable deployments for application and data teams. This position combines platform engineering expertise with DevOps practices and data-platform exposure, particularly concerning Kubernetes environments. What we offer: Contract Length: 12 months+ prolongation Type of contract: B2B Contract Work Model: Remote Main Responsibilities: Design and operate a Kubernetes-based internal platform for application and data workloads. Provide self-service deployment and runtime capabilities for engineering teams via standardized pipelines and templates. Build and maintain CI/CD pipelines as platform components, primarily using Azure DevOps YAML. Operate and evolve platform integrations for data systems , including Snowflake-based workloads. Ensure platform reliability, observability, and security across environments. Support multi-environment and multi-cloud deployments , primarily in Azure. Own operational aspects of the platform, including troubleshooting, incident response, and continuous improvements. Key Requirements: Kubernetes expertise (AKS and on-prem Kubernetes) Experience with CI/CD pipelines, notably Azure DevOps YAML Strong understanding of platform reliability, observability, and security Operational experience in multi-cloud environments (Azure preference) Nice to Have: Experience with Snowflake Familiarity with AWS/GCP Proficiency with Terraform Knowledge of Bash and Python Experience with AI technologies

🏢 Summary: The offer is for an AI DevOps Lead Engineer responsible for designing and managing cloud infrastructure on Azure and GCP with a strong focus on Infrastructure as Code and CI/CD automation. The role involves leading infrastructure initiatives, administering Kubernetes clusters, and implementing secure, scalable, and resilient cloud solutions. It is a long-term B2B contract with a hybrid work model in Cracow. 🗂️ Requirements: 4+ years experience in DevOps, SRE, or Cloud Engineering, Strong knowledge of Linux/UNIX systems, Production experience with GCP and/or Azure, Experience managing GKE and/or AKS clusters, Proficiency in Infrastructure as Code with Terraform, Experience building and maintaining CI/CD pipelines with Jenkins, Scripting skills in Python and/or Bash 📃 Skills: GCP, Azure, GKE, AKS, Terraform, Jenkins, Python, Bash, Linux, UNIX, CI/CD, IaC 🏢 Description: We are seeking an accomplished AI DevOps Lead Engineer with a strong foundation in cloud infrastructure management and DevOps practices. The ideal candidate will have over 4 years of experience in DevOps, SRE, or Cloud Engineering roles, with a proven record of designing and implementing robust cloud solutions, particularly on GCP and Azure platforms. Strong expertise in Infrastructure as Code (IaC) and CI/CD pipeline management is imperative, along with scripting capabilities in Python and Bash. What we offer: Long Term B2B Contract Rate: 200 PLN/ H +VAT Hybrid Cracow ( 1-2 times per week) Main Responsibilities: Design, build, and manage core infrastructure on Azure using IaC principles. Administer and enhance GKE and AKS clusters, ensuring security, scalability, and resilience. Evolve Jenkins pipelines and developer tooling for improved automation and efficiency. Implement security controls and automate vulnerabilities remediation. Develop a robust monitoring and alerting framework for operational visibility. Implement security gateways for improved governance. Key Requirements: 4+ years of experience in a DevOps, SRE, or Cloud Engineering role. Deep knowledge of Linux/UNIX operating systems. Production experience with GCP and/or Azure, including management of clusters (GKE, AKS). Strong proficiency with Infrastructure as Code using Terraform. Proven experience with CI/CD pipeline development using Jenkins. Scripting and automation skills in Python and/or Bash. Nice to Have: Experience with monitoring tools like Prometheus, Grafana, and Loki. Familiarity with container management using Docker. Knowledge of additional cloud services and platforms.

🏢 Summary: Remote AI Lead Data Engineer role responsible for designing and delivering enterprise-grade AI data platforms while leading a team of engineers. The position focuses on building scalable Lakehouse architectures, advanced MLOps frameworks, and LLM orchestration pipelines. It bridges Data Science and Data Engineering to ensure robust, governed, and production-ready AI infrastructure. 🗂️ Requirements: 8–10 years of Data Engineering experience, Minimum 3 years in technical lead role, Expert-level Python, Expert-level SQL, Expert-level PySpark in distributed environments, Experience with SageMaker, Azure ML, or Vertex AI, Hands-on MLflow or Kubeflow for CI/CD, Experience with Monte Carlo or Datadog, Experience with Collibra or Alation, Implementation of Responsible AI guardrails, Knowledge of Medallion, Data Mesh, Lakehouse architectures, Experience with PII masking and data lineage, Knowledge of HIPAA and GDPR compliance 📃 Skills: Python, SQL, PySpark, SageMaker, AzureML, VertexAI, MLflow, Kubeflow, MonteCarlo, Datadog, Collibra, Alation, Lakehouse, Medallion, DataMesh, CI/CD, LLM, HIPAA, GDPR 🏢 Description: This is a remote position. The AI Lead Data Engineer acts as the technical lighthouse for our data squads. With 8–10 years of experience, you are responsible for the technical design and delivery of robust AI data platforms. You will bridge the gap between Data Science and Data Engineering, ensuring that our infrastructure supports advanced MLOps and LLM requirements while leading a team of engineers to maintain elite coding and governance standards. Key Responsibilities: Technical Leadership: Lead a squad of data engineers in the design and execution of end-to-end AI data architectures. AI Observability & Governance: Build frameworks for bias detection, ethical AI considerations, and auditability using platforms like Collibra or Alation. Infrastructure Design: Lead the transition to Data Lakehouse architectures and implement feature stores for enterprise-wide model reuse. Delivery Management: Work with stakeholders to manage project milestones, technical risks, and on-time delivery. Advanced MLOps: Implement enterprise-grade CI/CD for ML workflows using MLflow or Kubeflow. GenAI Orchestration: Design specialized pipelines for LLM evaluation frameworks and prompt-tuning datasets. Requirements 8–10 years of experience with at least 3 years in a lead role managing technical delivery. Expert-level Python, SQL, and PySpark optimization for distributed environments. Deep experience with AI platform services such as Amazon SageMaker, Azure ML, or Vertex AI. Hands-on experience implementing enterprise observability with Monte Carlo or Datadog. Experience with data governance platforms (Collibra/Alation) and implementing Responsible AI guardrails. Deep understanding of modern data patterns (Medallion architecture, Data Mesh, Lakehouse). Advanced knowledge of security frameworks, including PII masking, data lineage, and HIPAA/GDPR compliance. Exceptional ability to mentor junior engineers and communicate complex data strategies to business 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