AI Platform Engineer (GCP)

🏢 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: 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: Long-term B2B opportunity for an AI DevOps Lead Engineer to design and manage cloud infrastructure on Azure and GCP, focusing on IaC, CI/CD, and Kubernetes clusters. The role centers on building secure, scalable environments, automating processes, and enhancing monitoring and security frameworks. Hybrid work model with strong emphasis on cloud-native and DevOps best practices. 🗂️ Requirements: 4+ years in DevOps, SRE, or Cloud Engineering, Strong knowledge of Linux/UNIX, Production experience with GCP and/or Azure, Experience managing GKE and/or AKS clusters, Proficiency in Terraform for Infrastructure as Code, Experience building CI/CD pipelines with Jenkins, Scripting skills in Python and/or Bash 📃 Skills: GCP, Azure, GKE, AKS, Terraform, Jenkins, Python, Bash, Linux, Kubernetes, CI/CD, IaC 🏢 Description: Introduction & Summary: 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. Other Details: This position offers the opportunity to work in a dynamic environment that fosters innovation and collaboration. Candidates can work remotely or on-site, depending on personal preferences; flexibility in schedule is provided to facilitate a productive work-life balance.

🏢 Summary: On-site role in Wroclaw for a Kubernetes & Cloud Infrastructure Engineer focused on building and operating scalable, secure AI platform infrastructure. The position centers on managing Kubernetes clusters, AWS environments, and infrastructure as code to support GPU workloads and large language model deployments. You will enhance reliability, automation, and observability of cloud-native AI systems. 🗂️ Requirements: 4+ years in Cloud, DevOps, or Platform Engineering, Strong expertise in Kubernetes cluster operations and multi-tenancy, Experience with GPU scheduling and model serving infrastructure, Hands-on experience with AWS (networking, IAM, EKS, EC2), Proficiency in Python, Experience with Terraform and infrastructure as code, Ability to build and operate CI/CD pipelines, Experience implementing GitOps workflows, Experience defining and managing infrastructure SLOs, Fluent English, Legal right to work in the EU 📃 Skills: Kubernetes, AWS, EKS, EC2, IAM, Terraform, Helm, Kustomize, Python, CI/CD, GitOps, GPU, Docker, Linux, Networking, Observability 🏢 Description: Unleash the power of cloud-native infrastructure — revolutionize AI platforms with your expertise! Wroclaw-based opportunity with on-site work model As a Kubernetes & Cloud Infrastructure Engineer – AI Platform , you will be working for our client, a leader in AI innovation, building and managing critical infrastructure that supports advanced AI models and large language model workloads. Your work will directly impact the delivery, scalability, and security of cutting-edge AI solutions, empowering teams across the firm to harness AI's full potential. Join us and be part of shaping the future of intelligent technologies! Your main responsibilities: Build and operate scalable Kubernetes clusters supporting multi-tenancy, GPU workloads, and model serving. Manage AWS infrastructure, including networking, IAM, security, and cost optimization. Develop and maintain infrastructure as code utilizing tools like Terraform, Helm, and Kustomize. Implement and maintain CI/CD and GitOps workflows to streamline deployment pipelines. Build observability solutions for system health, utilization, latency, and platform performance monitoring. Automate scaling, capacity management, and enforce security and governance policies across cloud and on-premise environments. Define and monitor infrastructure Service Level Objectives (SLOs) to ensure reliability and performance. Collaborate closely with AI Platform Engineers, Data Scientists, and Research teams to support model inference and deployment infrastructure. Enable internal teams through platform tooling, onboarding, and self-service portals. You're ideal for this role if you have: 4+ years of experience in Cloud, DevOps, or Platform Engineering. Strong expertise in Kubernetes, including cluster operations, multi-tenancy, GPU scheduling, and Helm/Kustomize. Hands-on experience with AWS cloud services—networking, IAM, EKS, EC2, and cost management. Proficient in Python and infrastructure-as-code tools such as Terraform. Proven ability to build and operate CI/CD and GitOps workflows. Skilled in defining and managing infrastructure SLOs. Pragmatic, ownership-driven approach and comfortable working in ambiguous environments. It is a strong plus if you have: Experience supporting LLM inference workloads, model serving platforms, or GPU-backed infrastructure. Knowledge of RAG systems, vector databases, or AI-related data platforms. Background in high-performance or latency-sensitive environments. Relevant certifications such as CKA, CKAD, Solutions Architect, or similar. Language Required for the role: Fluent English Eligibility to work in this role: Only candidates with an existing legal right to work in the European Union will be considered for this role. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data.

🏢 Summary: Remote AI Senior DevOps Engineer role focused on building and automating CI/CD and MLOps pipelines to enable seamless ML model deployment from training to production. The position bridges AI development and operations, emphasizing infrastructure as code, monitoring, DevSecOps, and scalable cloud environments. It involves close collaboration with AI teams to create a self-service model deployment platform. 🗂️ Requirements: 6–8 years experience in DevOps or SRE roles, Minimum 2 years experience in MLOps or AI/ML workloads, Expertise in Jenkins, GitHub Actions, or GitLab CI/CD, Hands-on experience with Azure DevOps, Hands-on experience with Terraform, Advanced knowledge of Docker and Kubernetes, Experience setting up Prometheus and Grafana dashboards, Experience with MySQL, PostgreSQL, or MongoDB, Familiarity with Ansible, Chef, or Puppet, Experience with SAST/DAST and vulnerability scanning in CI/CD, Experience with dataset and model versioning tools, Professional English C1 level 📃 Skills: Azure, Terraform, CloudFormation, Jenkins, GitHub, GitLab, Docker, Kubernetes, Prometheus, Grafana, MySQL, PostgreSQL, MongoDB, Ansible, Chef, Puppet, SAST, DAST, DVC, CI/CD, MLOps 🏢 Description: This is a remote position. Virtusa is seeking an AI Senior DevOps Engineer to bridge the gap between AI development and production-grade operations. You will be responsible for building the automated "highways" that allow ML models to flow from training to deployment seamlessly. This role requires a strong DevOps foundation combined with an understanding of the unique challenges of MLOps, such as GPU resource management, model versioning, and performance monitoring. Key Responsibilities: CI/CD & MLOps Pipelines: Build and maintain automated pipelines for ML models using Azure DevOps, GitHub Actions, or Jenkins. Workflow Automation: Automate model validation, packaging, and deployment workflows to ensure rapid iteration cycles. Infrastructure as Code (IaC): Use Terraform or CloudFormation to provision and manage cloud-native infrastructure, focusing on high-availability and scalability. Monitoring & Observability: Set up comprehensive monitoring for infrastructure (CPU/GPU/Memory) and model performance (latency and drift) using Prometheus and Grafana. DevSecOps Implementation: Integrate security into the heart of the pipeline, including secret management, IAM role configuration, and vulnerability scanning. Collaboration: Work closely with Data Scientists and AI Engineers to enable a self-service platform for model deployment. Requirements 6–8 years of experience in DevOps/SRE roles, with a minimum of 2 years focused on MLOps or supporting AI/ML workloads. Deep expertise in Jenkins, GitHub Actions, or GitLab CI/CD. Hands-on proficiency with Azure DevOps and Terraform (CloudFormation is a strong plus). Advanced knowledge of Docker and Kubernetes for managing distributed AI applications. Proven experience setting up Prometheus and Grafana dashboards for technical and model-specific metrics. Practical experience managing or connecting to MySQL, PostgreSQL, or MongoDB. Familiarity with Ansible, Chef, or Puppet for automated environment setup. Hands-on experience with SAST/DAST tools and automated vulnerability scanning within CI/CD pipelines. Experience with versioning tools for datasets and models (e.g., DVC or similar pipeline versioning logic). Professional English (C1) for seamless interaction with global delivery teams. 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: Junior Python AI Engineer role focused on building and deploying scalable, secure AI-driven solutions using Python and cloud platforms in a hybrid work model. The position involves developing AI applications, cloud-native microservices, and CI/CD pipelines while collaborating with cross-functional teams. It offers growth opportunities, certifications, and a comprehensive benefits package. 🗂️ Requirements: 6–12 months of commercial experience writing production-ready Python code, Experience with AI technologies (OpenAI/Anthropic APIs, model deployment, prompt engineering, RAG, Agentic AI), Experience with API development using FastAPI, Flask or Django, Experience with at least one cloud provider: AWS, Azure or GCP, Commercial experience with CI/CD tooling, Ability to troubleshoot bugs and optimize performance, Strong communication and teamwork skills 📃 Skills: Python, AI, OpenAI, Anthropic, RAG, FastAPI, Flask, Django, AWS, Azure, GCP, CI/CD, Microservices, Serverless, Cloud 🏢 Description: We are seeking a skilled Junior Python Engineer with experience in AI technologies to join a project for one of our key Clients. As Junior Python AI Engineer, you will develop and deploy robust, scalable, and secure solutions leveraging Python, AI and cloud technologies. You will work closely with cross-functional teams to create innovative software systems that solve complex business problems and drive digital transformation. This position offers a hybrid model of work, with 3 days per week working from our office located in Katowice. Responsibilities Develop and maintain high-quality software solutions Write clean, efficient, and well-documented Python code to build and maintain AI applications, tools and services Implement and manage cloud-based solutions using platforms such as AWS, Azure, or Google Cloud Platform (GCP) Develop scalable microservices and serverless applications using cloud-native tools and frameworks Ensure system reliability and scalability through robust coding practices, automated testing, and effective monitoring Collaborate with product, operations, and engineering teams to gather requirements, refine features, and design solutions Implement CI/CD pipelines to streamline application deployment and delivery on cloud environments Troubleshoot production issues and optimize performance Stay current with Python and AI development trends, cloud technologies, and emerging tools Requirements 6 to 12 months of commercial experience writing production-ready, clean Python code Experience working with AI technologies (e.g., API integration of OpenAI/Anthropic, deploying models, prompt engineering, RAG, Agentic AI) Exposure to API development using frameworks like FastAPI, Flask or Django Experience working with at least one major cloud provider: AWS, Microsoft Azure, or Google Cloud Platform (GCP) Commercial experience utilizing Continuous Integration and Continuous Deployment tooling A proactive approach to troubleshooting bugs, optimizing performance, and resolving deployment bottlenecks Strong communication and collaboration skills in a team-oriented environment We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Senior GCP Cloud Engineer role focused on building, automating, and securing scalable cloud infrastructure on Google Cloud Platform. The position involves managing GKE clusters, developing Terraform-based infrastructure as code, and implementing high-performance CI/CD pipelines with a strong DevSecOps approach. The engineer is responsible for cloud networking, security, and observability to ensure resilient, production-ready environments. 🗂️ Requirements: 6+ years DevOps/Cloud experience, Hands-on experience with GCP services (GKE, ComputeEngine, CloudSQL, IAM), Strong Terraform proficiency, Strong Kubernetes knowledge, Docker experience, Experience with CI/CD pipeline automation, Experience integrating security into CI/CD workflows, Knowledge of cloud networking (VPC, Firewalls), Experience with monitoring and logging tools, Legal work permit in Poland 📃 Skills: GCP, GKE, ComputeEngine, CloudSQL, CloudStorage, IAM, Terraform, Kubernetes, Docker, CICD, GitHubActions, GitLab, Jenkins, DevSecOps, VPC, Firewalls, CloudArmor, SecretManager, CloudMonitoring, CloudLogging 🏢 Description: Project info: We are seeking a Senior GCP Cloud Engineer to drive the implementation, automation, and security of our cloud infrastructure. In this role, you will be the technical engine behind our Google Cloud Platform (GCP) environment, responsible for building scalable GKE clusters, robust Terraform modules, and high-velocity CI/CD pipelines. You should be a hands-on expert who defaults to automation, possesses a “security-first” mindset, and can translate architectural blueprints into production-ready, resilient code. Responsibilities: 1. GCP Service Management Deployment & Scaling: Manage and optimize core GCP services including Compute Engine (MIGs), Cloud SQL (backups/replication), and Cloud Storage. Identity & Access: Implement and maintain granular IAM policies and service account permissions to ensure least-privileged access across all environments. 2. Kubernetes & Container Orchestration GKE Operations: Manage the full lifecycle of Google Kubernetes Engine (GKE) clusters, including upgrades, autoscaling configuration, and resource monitoring. Containerization: Build and secure Docker images and manage container orchestration using Kubernetes best practices (Ingress, ConfigMaps, Secrets). 3. Infrastructure as Code (IaC) & DevSecOps Terraform Development: Write and maintain modular, reusable Terraform code to provision and manage cloud resources as a single source of truth. Pipeline Automation: Build and optimize CI/CD pipelines that automate testing, deployment, and DevSecOps security scanning (using GitHub Actions, GitLab, or Jenkins). 4. Networking, Security & Monitoring Cloud Networking: Configure and troubleshoot Cloud Networking components, including VPCs, Shared VPCs, Firewalls, and Cloud Load Balancing. Security & Compliance: Implement cloud-native security tools (Cloud Armor, Secret Manager) to protect applications and data. Monitoring & Alerting: Design and manage observability dashboards using Cloud Monitoring and Cloud Logging to ensure proactive issue detection and system reliability. Job requirements: 6+ Years in DevOps/Cloud: Proven experience managing production-grade cloud environments with a focus on GCP. GCP Services Expertise: Hands-on experience with GKE, Compute Engine, Cloud SQL, and IAM. (Associate or Professional Cloud Engineer certification is a plus). IaC Specialist: Strong proficiency in Terraform for infrastructure automation. K8s Expert: Solid understanding of Kubernetes architecture, container orchestration, and Docker. DevSecOps Mindset: Experience integrating security checks into automated CI/CD workflows. Networking & Monitoring: Practical knowledge of cloud networking (VPC/Firewalls) and system monitoring tools. Must possess a legal work permit in Poland Benefits: General benefits - depends on the form of employment Hybrid work model combining office & remote work Attractively located office with collaboration spaces Onsite parking space for employees Referral program with financial bonus Life Insurance Budget for development (including language courses and others), clear career path with the possibility to gain experience in international environment Access to internal Learning Platform with multiple trainings oriented for professional growth Lifestyle benefits: Access to MyBenefit platform (Multisport included) Team Building activities Charity initiatives Working environment promoting diversity and inclusion Health benefits: Private medical care - Platinum Package

🏢 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: The offer is for a Senior Cloud Native Developer to design and deliver scalable, secure cloud-native applications with AI at the core. The role focuses on Python-based microservices, cloud platforms, infrastructure automation, observability, and building AI-powered solutions such as LLM applications and RAG pipelines. It combines deep software engineering expertise with hands-on cloud and AI integration experience. 🗂️ Requirements: 3+ years of hands-on software development experience with strong focus on Python, Proven experience designing, developing and deploying microservices applications, Strong knowledge of cloud-native principles, Hands-on experience with cloud services including containerization and serverless computing, Deep experience with at least one cloud platform: Azure, AWS or GCP, Experience implementing application monitoring and logging, Practical experience with AI-powered development tools, Experience building AI-integrated solutions using LLM APIs, RAG pipelines or AI agents, English proficiency at Upper-Intermediate (B2) level or higher 📃 Skills: Python, Microservices, Azure, AWS, GCP, Docker, Kubernetes, Serverless, CI/CD, IaC, Monitoring, Logging, LLM, RAG, OpenAI, AzureOpenAI, GitHubCopilot, LangChain, LangGraph, LlamaIndex, Pinecone, pgvector 🏢 Description: We are looking for a Senior Cloud Native Developer passionate about building scalable, resilient, and observable cloud-native applications with AI at the core. The ideal candidate combines deep Python expertise with hands-on cloud engineering experience and the ability to design and deliver AI-powered solutions. Responsibilities Design, implement, and deploy cloud-native solutions using Python, with a focus on scalability, security, performance, and containerization or serverless architectures Design managed database solutions for efficient data management Implement observability through monitoring and logging Apply Infrastructure as Code principles to automate cloud infrastructure management and provisioning Drive continuous integration and deployment practices for rapid and automated application delivery Design and build AI-integrated solutions, including LLM-based applications, RAG pipelines, and AI agents Requirements 3+ years of hands-on experience in software development with a strong emphasis on Python Proven experience designing, developing, and deploying microservices applications Strong knowledge of cloud-native principles and hands-on experience with cloud services, including containerization and serverless computing Deep Experience with cloud platform (Azure, AWS, or GCP) Hands-on experience implementing application monitoring and logging Practical AI knowledge across two dimensions: leveraging AI-powered development tools (GitHub Copilot, Cursor, or similar) to accelerate delivery, and experience building AI-integrated solutions (LLM APIs, RAG pipelines, AI agents, or integrations with Azure OpenAI / OpenAI) English language proficiency at Upper-Intermediate level (B2) or higher Nice to have Cloud platform certifications (Azure, AWS, or GCP) Experience with AI/LLM frameworks and tooling: LangChain, LangGraph, LlamaIndex, vector stores (Azure AI Search, pgvector, Pinecone) Familiarity with AI orchestration patterns: multi-agent systems, evaluator-optimizer loops, retrieval-augmented generation Knowledge of advanced cloud-native architectures We offer/Benefits We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: DevOps Engineer role focused on designing and maintaining AI-driven CI/CD pipelines and deploying machine learning models across cloud and hybrid environments. The position involves integrating AI/ML tools into DevOps processes, optimizing infrastructure for AI workloads, and ensuring security and high availability. The engineer will work with modern cloud platforms and data technologies in international, agile projects. 🗂️ Requirements: Bachelor’s degree in Engineering, IT, Science or related field, Minimum 5 years of experience in DevOps or similar role, Hands-on experience with DevOps tools in AI/ML workflows, Experience with cloud platforms and AI/ML services, Experience deploying and scaling ML models in production, Proficiency in scripting or programming languages, Experience implementing automated testing for AI workflows, Knowledge of secure environments for AI-driven systems 📃 Skills: Jenkins, GitHubActions, Kubernetes, Docker, Terraform, AWS, Azure, GCP, MLflow, Kubeflow, Airflow, Python, Bash, YAML, TensorFlow, PyTorch, Scikit-learn, Grafana, AIOps 🏢 Description: About the role As a DevOps Engineer with AI integration skills, you will collaborate across multiple implementation streams and work closely with agile teams to achieve project and client goals. We are looking for passionate engineers ready to move our projects to the next level by leveraging modern technology stacks and AI-driven solutions. You will participate in international projects based on the latest data technologies and cloud platforms. Your key responsibilities Design and maintain CI/CD pipelines incorporating AI/ML tools and frameworks. Collaborate with AI teams to deploy and scale machine learning models in production environments. Integrate AI-based monitoring, alerting, and analytics tools to improve pipeline visibility and enable predictive analysis. Optimize infrastructure resource utilization for AI applications across cloud, on-premises, and hybrid environments. Ensure strong security practices within AI-driven pipeline ecosystems. Troubleshoot pipeline and infrastructure issues, especially those involving AI components, and ensure high availability. Monitor system performance and implement improvements using AI-enhanced tools. Skills and attributes for success Hands-on experience with DevOps tools such as Jenkins, GitHub Actions, Kubernetes, Docker, and Terraform. Strong understanding of cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services. Familiarity with AI workflow tools such as MLflow, Kubeflow, or Airflow. Proficiency in scripting and programming languages (Python, Bash, YAML, etc.). Ability to implement automated testing frameworks for validating AI models and workflows. Experience building secure environments for AI-driven systems. Experience integrating AI-powered monitoring tools (AIOps, Grafana with ML plugins, or custom AI diagnostics). Requirements Bachelor’s degree in Engineering, IT, Science, or a related technical field. At least 5 years of experience in a corporate IT environment in a similar role. Proven experience with DevOps tools and frameworks used in AI/ML workflows. Strong communication skills and ability to collaborate with global teams. Nice to have Certifications in DevOps or AI/ML (e.g., Kubernetes, AWS Machine Learning Specialty). Experience working with AIOps platforms. Knowledge of specialized data pipeline automation tools for machine learning. Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn in production environments.