AI Senior DevOps 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: Remote Senior FullStack Developer role focused on building and scaling end-to-end AI applications, agentic workflows, and modern front-end interfaces. The position involves designing AI-driven solutions, optimizing system architecture, and integrating LLM-based systems into production environments. You will work on data-heavy applications and enterprise automation within a fully remote project in Poland. 🗂️ Requirements: 5+ years of experience with Python for data-heavy or AI-integrated applications, Strong experience with Django, Flask or FastAPI, Strong mastery of Vanilla JavaScript, Hands-on experience with AngularJS and knowledge of migration to modern Angular, Experience building agentic AI systems and autonomous LLM-based workflows, Practical knowledge of LangChain, LlamaIndex and RAG, Experience with AI agent orchestration frameworks, Commercial experience with GCP or AWS, Proven experience with Google AppScript for enterprise automation, Strong understanding of RESTful APIs, Experience with asynchronous programming, Experience with end-to-end agentic workflows, Hands-on experience with GenAI technologies such as Gemini, Copilot or Claude 📃 Skills: Python, Django, Flask, FastAPI, JavaScript, AngularJS, Angular, LangChain, LlamaIndex, RAG, LLM, GCP, AWS, AppScript, REST, GenAI, Gemini, Copilot, Claude 🏢 Description: This is a remote position. As a Senior FullStack Developer at Virtusa , you will build and scale end-to-end AI applications, integrate automated workflows, and design intuitive front-end interfaces. You will diagnose architectural bottlenecks, propose AI-driven optimizations, and communicate directly with stakeholders to turn complex requirements into functional code. This is a fully remote project within Poland. Requirements At least 5 years of experience with Python (Django, Flask, or FastAPI), specifically for data-heavy or AI-integrated applications. Strong mastery of Vanilla JavaScript and hands-on experience with Angular JS (and familiarity with the migration path to modern Angular). Hands-on experience building agentic AI systems and autonomous workflows based on LLMs. Strong practical knowledge of: LangChain, LlamaIndex, RAG, AI agent orchestration frameworks. Commercial cloud experience: GCP (preferred) or AWS AppScript Expertise: Proven experience using Google AppScript for enterprise automation or custom add-ons. API Design: Deep understanding of RESTful APIs and asynchronous programming. Experience in end to end agentic workflows Strong experience in using Gen AI technologies : Gemini, co-pilot, claude AI Benefits Professional training programs Work with a team that is recognized for its excellence. We have been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We have also received the Great Place To Work® certification for seven years in a row

🏢 Summary: Remote Senior FullStack Developer role focused on building and scaling end-to-end AI applications with agentic workflows and intuitive front-end interfaces. The position involves designing AI-driven optimizations, integrating LLM-based systems, and developing data-heavy backend services. The role requires close collaboration with stakeholders to translate complex requirements into production-ready solutions. 🗂️ Requirements: Minimum 5 years of experience with Python (Django, Flask, or FastAPI), Experience building data-heavy or AI-integrated applications, Strong proficiency in Vanilla JavaScript, Hands-on experience with AngularJS and knowledge of migration to modern Angular, Experience building agentic AI systems based on LLMs, Practical knowledge of LangChain, LlamaIndex, RAG, and AI orchestration frameworks, Commercial cloud experience with GCP or AWS, Proven experience with Google AppScript for enterprise automation, Strong understanding of RESTful APIs, Experience with asynchronous programming, Experience designing end-to-end agentic workflows, Hands-on experience with Generative AI tools such as Gemini, Copilot, or Claude 📃 Skills: Python, Django, Flask, FastAPI, JavaScript, AngularJS, Angular, LangChain, LlamaIndex, RAG, LLM, GCP, AWS, AppScript, REST, Gemini, Copilot, Claude 🏢 Description: This is a remote position. As a Senior FullStack Developer at Virtusa , you will build and scale end-to-end AI applications, integrate automated workflows, and design intuitive front-end interfaces. You will diagnose architectural bottlenecks, propose AI-driven optimizations, and communicate directly with stakeholders to turn complex requirements into functional code. This is a fully remote project within Poland. Requirements At least 5 years of experience with Python (Django, Flask, or FastAPI), specifically for data-heavy or AI-integrated applications. Strong mastery of Vanilla JavaScript and hands-on experience with Angular JS (and familiarity with the migration path to modern Angular). Hands-on experience building agentic AI systems and autonomous workflows based on LLMs. Strong practical knowledge of: LangChain, LlamaIndex, RAG, AI agent orchestration frameworks. Commercial cloud experience: GCP (preferred) or AWS AppScript Expertise: Proven experience using Google AppScript for enterprise automation or custom add-ons. API Design: Deep understanding of RESTful APIs and asynchronous programming. Experience in end to end agentic workflows Strong experience in using Gen AI technologies : Gemini, co-pilot, claude AI Benefits Professional training programs Work with a team that is recognized for its excellence. We have been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We have also received the Great Place To Work® certification for seven years in a row

🏢 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.

🏢 Summary: Senior DevOps Engineer role focused on AI and platform operations, ensuring production stability, CI/CD pipeline management, and Infrastructure as Code implementation. The position involves supporting AI/ML workloads, enhancing observability, and driving automation and self-healing infrastructure solutions. The role combines operational leadership with hands-on DevOps and MLOps practices in complex production environments. 🗂️ Requirements: Hands-on experience with Docker and Kubernetes, Experience with CI/CD tools including Jenkins and Maven, Experience with Infrastructure as Code using Ansible, Experience with relational databases such as Oracle and DB2, Knowledge of Spring, Hibernate, XML, JSON, Kafka, Advanced troubleshooting using Splunk, Apica, Sysdig, Experience with Prometheus, Grafana, ELK stack, Experience with MLOps and AI/ML workload deployments, Knowledge of AI model serving and ML containerization, Understanding of AI agent orchestration and workflow automation 📃 Skills: Docker, Kubernetes, Jenkins, Maven, Ansible, Oracle, DB2, Spring, Hibernate, XML, JSON, Kafka, Splunk, Apica, Sysdig, Prometheus, Grafana, ELK, MLOps, AI, ML 🏢 Description: As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for: Senior DevOps Engineer (AI & Platform Operations) Responsibilities: Incident & Problem Management: Lead RCA processes and implement preventive measures Production Support: Monitor, analyze, and optimize service performance and stability CI/CD Management: Build, maintain, and enhance deployment pipelines for multiple APIs Environment Management: Maintain Pre-Production and Production environments Cross-team Collaboration: Work closely with Platform Operations teams and delivery factory Documentation: Build comprehensive runbooks and knowledge base for operational procedures Innovation Leadership: Evaluate and implement new DevOps tools, practices, and AI-powered solutions Implement Infrastructure as Code practices Drive automation and self-healing infrastructure solutions Support AI/ML workload deployments and operations Lead adoption of emerging technologies and best practices Requirements: Hands‑on experience with Docker containerization and Kubernetes orchestration Experience working with CI/CD tools, including Jenkins and Maven Experience with Infrastructure as Code using Ansible Experience working with relational databases such as Oracle and DB2 Basic knowledge of application technologies including Spring, Hibernate, XML, JSON, and Kafka Advanced troubleshooting experience using Splunk, Apica, and Sysdig Experience with modern observability tools, such as Prometheus, Grafana, and preferably the ELK stack Experience with AI/ML operations (MLOps) and AI agent deployments Knowledge of AI model serving platforms and ML workload containerization Understanding of AI agent orchestration and workflow automation Experience implementing innovative solutions using emerging technologies Ability to evaluate and integrate new DevOps tools and practices Very good command of English, both spoken and written Nice to have: Software development knowledge in Java / J2EE Experience working with cloud platforms, such as AWS, Azure, or GCP Experience with IBM DataStage Offer: Private medical care Co-financing for the sports card Constant support of dedicated consultant Employee referral program

🏢 Summary: The offer is for a Senior DevOps Engineer responsible for designing, building, and operating secure, scalable cloud infrastructure for AI-driven automation platforms. The role focuses on Infrastructure as Code, CI/CD, monitoring, and automation in enterprise cloud environments, ensuring reliability, security, and compliance. It combines hands-on engineering with ownership of mission-critical services across their full lifecycle. 🗂️ Requirements: University degree in informatics or equivalent professional experience, Minimum 7 years of DevOps or infrastructure experience, Proven experience with Infrastructure as Code using Terraform, Experience with CI/CD tools such as Jenkins or GitHub Actions, Hands-on experience with AWS or Azure cloud services, Experience with DevOps workflows and automated incident response, Experience managing enterprise private cloud environments, Knowledge of secure service-to-service communication patterns, Knowledge of modern authentication protocols, Experience with monitoring, logging, and alerting systems, Experience with Python or another programming language, Understanding of AI technologies and AI process automation, Fluency in Polish and English (minimum B2) 📃 Skills: Terraform, Jenkins, GitHub, AWS, Azure, Python, CI/CD, DevOps, IaC, Monitoring, Logging, Alerting, Authentication, AI, Cloud 🏢 Description: As a Senior DevOps Engineer (AI & Automation Platform), you will be responsible for building and maintaining secure, scalable cloud infrastructures that power AI-driven automation. In this role, you will design and operate enterprise-ready solutions, implement Infrastructure as Code practices, and drive automation across systems and workflows. You will collaborate with internal teams and external vendors, ensuring performance, reliability, and compliance while mentoring colleagues and fostering an agile, innovation-oriented culture. This position is ideal for a hands-on engineer with strong analytical skills, a passion for automation, and the ability to take ownership of mission-critical services. Your Key Responsibilities Building and maintaining scalable and reliable cloud infrastructure for AI process automation platforms Ensuring operable and securing cloud-based solution architecture for custom-developed, open-source, and off-the-shelf applications Acting as technical consultant for internal colleagues and collect their feedback to ensure a successful user experience Establishing and maintaining logging, monitoring and alerting systems to proactively identify and resolve performance issues Taking on the technical responsibility of applications throughout the life cycle as part of a DevOps team Driving improvements of the automation level of our operations towards self-service Close collaboration with external software vendors for managing, developing, and maintaining IT systems Building and maintaining disaster recovery and business continuity plans for mission-critical applications and infrastructure Ensuring compliance with security policies and standards, working with security and compliance teams as necessary Your Qualifications University degree in (business) informatics or alternative training with relevant professional experience in this field At least 7 years of relevant professional experience in this field Strong automation and infrastructure as code mindset backed by proven experience in using Terraform and CI/CD technologies like Jenkins or GitHub Actions Experience with DevOps workflows for infrastructure management and automated incident response Proven experience in installing, configuring, maintaining and managing support operations with third party software in secured and enterprise ready private cloud environments Profound knowledge about common patterns for secure service-to-service connectivity and modern authentication protocols Familiarity with common monitoring, logging, and alerting solutions Hands-on experience working with managed cloud services (AWS or Azure preferred), including compute, storage, databases, and AI services Strong understanding of latest AI technology, like AI Agents, in combination with AI process automation Experience with an additional programming language such as Python Fluency in both Polish and English, with a minimum of B2 level proficiency Knowledge of German is a plus Ability and willingness to coach and to take responsibility for services Strong analytical skills with the ability to collect, organize, analyze and disseminate significant amounts of information with attention to detail and accuracy Eager to learn new technologies and skills (T-Shape philosophy) Proficiency in agile methodologies, with experience working effectively within agile teams and environments, fostering an agile mindset in daily work Willingness to travel up to 10%  of the time for work Our Offer Be a part of a global company & international team with a diverse variety of backgrounds, skills and views. As part of our IT team, you will actively shape the technology and solutions used by Schaeffler Grow with us! Get access to training platforms, internal & external trainings, supporting experts and the real-life challenges , where you will put all your skills in practice. We work in a hybrid working model (or a fully remote in a special cases) with flexible working hours . Our modern office is located in the center of Wroclaw . We offer attractive benefits package, such as medical and dental care , sports card, life insurance for you and your family. We are also providing access to our Mental Comfort Program. Our Cafeteria Platform allows you to choose from various benefit options with points monthly added to your account. Haven’t found what you are looking for? Our concierge will be happy to help! Join our CSR activities, such as tree planting, riverside cleanup, or participate in other charity events. Spend some time with your work colleagues during integrational events such as mountain trekking, city games and workshops. You can join also one of our many Passion Clubs like Foodies, Sports Team and Language Clubs as well!

🏢 Summary: Remote Senior DevOps Engineer role focused on modernizing and scaling a cloud-native Data & AI Platform. The position involves refactoring AWS and Airflow infrastructure, implementing Infrastructure as Code for Snowflake, and building next-generation workflow orchestration. The role also supports CI/CD automation and infrastructure for Data Science, ML, and AI systems. 🗂️ Requirements: Strong experience with AWS, Strong experience with Terraform, Hands-on experience with Apache Airflow, Experience with CI/CD tools (GitLab, GitHub Actions, Jenkins), Experience with Snowflake and Infrastructure as Code, Knowledge of modern workflow orchestration tools (Prefect, Dagster, Temporal), Experience supporting Data Science, ML, or AI platforms 📃 Skills: AWS, Terraform, Airflow, Snowflake, GitLab, GitHubActions, Jenkins, Prefect, Dagster, Temporal, CI/CD, IaC, Python 🏢 Description: Senior DevOps Engineer (Data Platform & AI) 📍 Remote from Poland We are looking for a Senior DevOps Engineer to support the evolution of our Data & AI Platform. Key responsibilities: • Refactoring AWS-based Data Platform infrastructure • Refactoring and optimization of Apache Airflow infrastructure • CI/CD runner setup and automation • Infrastructure setup for Data Science and ML pipelines • Infrastructure as Code (Terraform) for Snowflake environments • Design and implementation of a next-generation workflow engine to replace Airflow • Infrastructure setup for AI systems, including MCP servers Requirements: • Strong AWS and Terraform experience • Hands-on experience with Airflow infrastructure • CI/CD expertise (GitLab, GitHub Actions, Jenkins) • Experience with Snowflake and Infrastructure as Code • Understanding of modern workflow orchestration tools (Prefect, Dagster, Temporal, etc.) • Experience supporting Data Science, ML, or AI platforms Nice to have: • GCP / BigQuery exposure • Experience with LLM or AI infrastructure This is an opportunity to build and modernize a cloud-native data platform while helping shape the future AI infrastructure of the organization.

🏢 Summary: Hands-on DevOps Engineer role focused on building and operating automation, deployment, and reliability standards for large-scale GPU infrastructure supporting AI training and inference. The position involves Infrastructure as Code, CI/CD, observability, security, and low-level automation across bare-metal servers, networking, storage, and Kubernetes-based platforms. The role emphasizes reliability, scalability, and automation in complex, high-performance environments. 🗂️ Requirements: 4–7 years in DevOps, SRE, or Platform Engineering, Experience with infrastructure automation in production environments, Hands-on experience with Terraform or Ansible, Experience building and maintaining CI/CD pipelines, Knowledge of GitOps practices, Understanding of infrastructure security and vulnerability management, Experience with security tools (e.g., Snyk, CrowdStrike), Practical experience with Kubernetes, Experience with GPU technologies (e.g., NVIDIA GPU Operator, MIG), Scripting or programming skills in Python, Go, or Bash, Experience with bare-metal provisioning or low-level infrastructure automation, Knowledge of observability tools (Prometheus, Grafana, Loki, OpenTelemetry) 📃 Skills: Terraform, Ansible, Kubernetes, Python, Go, Bash, Prometheus, Grafana, Loki, OpenTelemetry, Snyk, CrowdStrike, NVIDIA, MIG, CI/CD, GitOps 🏢 Description: About the role We are looking for a DevOps Engineer to help build and operate automation, deployment, and reliability standards for large-scale GPU infrastructure used for AI training and inference workloads. In this role, you will work on software-defined infrastructure supporting GPU clusters, high-performance networking, storage platforms, and internal AI services. This is a hands-on position for someone who is comfortable working close to infrastructure, improving operational processes, and building reliable automation in a complex technical environment. Responsibilities Design, implement, and maintain Infrastructure as Code solutions for provisioning and managing bare-metal GPU servers, networking, storage, and cluster orchestration components Build and improve CI/CD pipelines for infrastructure, platform services, and internal tooling Develop and maintain monitoring, logging, alerting, and observability solutions for large-scale GPU environments Support reliability initiatives by defining and tracking SLIs/SLOs , automating incident response, and contributing to post-incident analysis Automate operational tasks such as cluster scaling, firmware and BIOS updates, hardware validation, diagnostics, and capacity planning Work closely with Infrastructure, Networking, Facilities, and AI/ML teams to ensure stable and scalable platform operations Support DevSecOps practices, including infrastructure hardening, vulnerability management, and compliance automation Identify repetitive manual work and replace it with efficient automation Evaluate new tools and solutions related to GPU infrastructure, orchestration, and cloud-native operations Requirements 4–7 years of experience in DevOps, SRE, Platform Engineering , or a similar role Strong practical experience with infrastructure automation in complex production environments Good hands-on knowledge of Terraform, Ansible , or similar Infrastructure as Code tools Experience building and maintaining CI/CD pipelines and working with GitOps practices Good understanding of infrastructure security, vulnerability management, and security best practices Experience with security tools such as Snyk, CrowdStrike , or similar solutions Practical experience with Kubernetes Experience working with GPU-related technologies such as NVIDIA GPU Operator, device plugins, MIG, or time-slicing Good scripting or programming skills in Python, Go, or Bash Experience with bare-metal provisioning, low-level infrastructure automation, or data center operations Good knowledge of observability tools such as Prometheus, Grafana, Loki, and OpenTelemetry Ability to work independently, prioritize tasks, and communicate effectively with technical teams English proficiency at least at a communicative level is required, as you will be working in an international team Nice to have Experience in AI infrastructure, HPC environments, hyperscale infrastructure, or data center operations Familiarity with orchestration and scheduling tools such as Slurm, Ray, Run:ai, KServe , or Kubernetes-based schedulers Experience integrating telemetry from power, cooling, or environmental systems Experience building internal platforms or self-service tools for engineering teams Understanding of compliance and audit requirements in security-sensitive environments What we offer Benefits package Opportunity to work on advanced infrastructure supporting large-scale AI workloads Real impact on the reliability and scalability of next-generation compute environments Collaboration with experienced engineers across infrastructure, platform, and AI domains A fast-moving environment with space for ownership, technical input, and professional growth

🏢 Summary: Junior DevOps Engineer role focused on supporting and automating cloud infrastructure for AI training and inference workloads. The position involves working with CI/CD pipelines, containerization, Infrastructure as Code, and monitoring systems in a hands-on learning environment. It offers growth in DevOps, platform engineering, and cloud operations. 🗂️ Requirements: 0–2 years in DevOps, IT operations, infrastructure, or system administration, Knowledge of Linux and terminal usage, Knowledge of Python for automation and scripting, Ability to write automation scripts, Practical knowledge of AWS and basic cloud services, Understanding of cloud infrastructure concepts, Knowledge of Docker and containerization, Basic understanding of CI/CD concepts, Ability to use Git, Basic understanding of networking, security, logging, and monitoring, Interest in Infrastructure as Code tools (Terraform or Ansible), Basic understanding of Kubernetes, Communicative English 📃 Skills: Linux, Python, AWS, Docker, CI/CD, Git, Terraform, Ansible, Kubernetes, Bash, Prometheus, Grafana, Loki, OpenTelemetry, GitHub, GitLab, Jenkins 🏢 Description: About the role We are looking for a Junior DevOps Engineer to support the development, automation, and maintenance of infrastructure used for AI training and inference workloads. In this role, you will work with experienced engineers on cloud and infrastructure automation, CI/CD pipelines, application environments, monitoring, and operational support. This is a hands-on position for someone who wants to grow in DevOps, platform engineering, cloud infrastructure, and modern operations. Responsibilities Support the maintenance and development of cloud and infrastructure environments Help prepare, maintain, and troubleshoot application environments Automate repetitive tasks using Python, Bash, and scripts Support the creation and maintenance of CI/CD pipelines Assist with Infrastructure as Code solutions for servers, networking, storage, and cluster components Monitor systems, analyze logs, and help troubleshoot technical issues Work with development, infrastructure, networking, and AI/ML teams on application deployment and platform operations Support the stability, security, and reliability of infrastructure Help identify manual processes that can be automated Document technical solutions, runbooks, and operational processes Requirements 0–2 years of experience in DevOps, IT operations, infrastructure, system administration, or a similar area Good knowledge of Linux and working in the terminal Good knowledge of Python for automation, scripts, and simple internal tools Ability to write clear scripts automating repetitive tasks Practical knowledge of AWS and basic cloud services Understanding of cloud environments and basic cloud infrastructure concepts Good knowledge of Docker and application containerization Basic understanding of CI/CD concepts Ability to work with Git Basic understanding of networking, security, logs, and monitoring Interest in Infrastructure as Code tools such as Terraform or Ansible Basic understanding of Kubernetes or willingness to learn Strong problem-solving attitude and eagerness to learn Ability to communicate clearly and work in a technical team Communicative English, as you will work in an international environment Nice to have First experience with Kubernetes, Terraform, Ansible, or GitOps Familiarity with monitoring tools such as Prometheus, Grafana, Loki, or OpenTelemetry Basic understanding of DevSecOps practices and vulnerability management Familiarity with AI infrastructure, GPU environments, HPC, or data center operations Experience with GitHub Actions, GitLab CI, Jenkins, or similar tools Interest in platform engineering, SRE, or large-scale infrastructure What we offer Benefits package Opportunity to learn from experienced infrastructure, platform, cloud, and AI engineers Work on modern infrastructure supporting AI workloads Space for professional growth in DevOps and platform engineering Remote or hybrid work from Poland

🏢 Summary: Lead AI Forward Deployment Engineer role focused on deploying, securing, and scaling AI solutions in enterprise environments using Google Cloud. The position bridges AI R&D and production by architecting Vertex AI pipelines, managing GKE clusters, and integrating AI into existing systems. It involves leading technical deployments and ensuring robust security for large-scale AI workloads. 🗂️ Requirements: 10+ years experience in Distributed Systems, Data Engineering, or DevOps, Expert-level knowledge of GCP and Vertex AI, Proven experience with GKE, Helm, and Istio, Strong Python experience with asynchronous and scalable backend development, Hands-on experience securing endpoints and AI systems, Experience designing end-to-end AI pipelines, Ability to manage GPU/TPU workloads, Legal work permit in Poland 📃 Skills: GCP, VertexAI, GKE, Kubernetes, Helm, Istio, Python, APIs, Microservices, DistributedSystems, DevOps, FeatureStore, Pipelines, ModelGarden, CloudArmor, ModelArmor, WAF, GPU, TPU, Networking, VPC 🏢 Description: Project info: We are seeking a skilled Lead AI Forward Deployment Engineer (GCP) to join our client's team. As a “Special Ops Engineer”, you will bridge the gap between our AI R&D and enterprise production. You will deploy, secure, and scale AI solutions within complex client environments using the Google Cloud ecosystem. Responsibilities: Production AI: Architect end-to-end pipelines on Vertex AI (Model Garden, Pipelines, and Feature Store). Security Hardening: Implement Model Armor for LLM safety (prompt injection/PII filtering) and Cloud Armor for edge-layer WAF protection. Orchestration: Design and manage high-scale Google Kubernetes Engine (GKE) clusters, optimizing for GPU/TPU workloads. Integration: Write production-grade Python microservices and APIs to embed AI into existing enterprise workflows. Client Leadership: Lead technical deployments on-site or in-client VPCs, navigating complex networking and legacy constraints. Job requirements: 10+ Years Engineering: Deep background in Distributed Systems, Data Engineering, or DevOps. GCP Mastery: Expert-level knowledge of Vertex AI and the broader GCP ecosystem. K8s Expert: Proven experience with GKE, Helm, and Service Mesh (Istio). Python Veteran: Master of asynchronous programming and scalable backend design. Security Expert: Hands-on experience securing endpoints and managing AI-specific vulnerabilities. Must possess a legal work permit in Poland Benefits: General benefits - depends on the form of employment Hybrid work model & 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