Senior Software Engineer

🏢 Summary: Technical role supporting an AI platform that automates and scales ML processes, focused on maintaining and developing documentation infrastructure and API docs generation. The position involves working with OpenAPI specifications, static site generators, and CI/CD pipelines to ensure high-quality, automated documentation delivery. Includes participation in on-call rotations and collaboration within modern DevOps-driven environments. 🗂️ Requirements: Proven experience with MkDocs and MkDocs-Material, Proficiency in Python, Experience with static site generators, Experience generating API documentation from OpenAPI spec, Strong knowledge of REST API principles, Experience with Git and GitHub workflows, Experience with CI/CD pipelines and GitHub Actions, Scripting skills for task automation, Understanding of dependency management tools (e.g., Poetry), Availability for on-call duty (5 AM–5 PM CEST, once every six weeks) 📃 Skills: Python, MkDocs, Material, OpenAPI, REST, Swagger, Redoc, Git, GitHub, CI/CD, GitHubActions, Poetry, Markdown, Docker, Bash, Shell, HTML, CSS, JavaScript, WCAG 🏢 Description: We’re Devopsbay - MLOPS, DevOps and AI Specialists. We know how nodes works, how to make the cloud cheaper or adapt AI to boost any area that companies need (any many more). We support our clients with strong engineers on a project basis and are always on the lookout for stellar performers. Our clients are at the cutting edge of modern solutions. We also develop our inhouse products: https://descrb.com/ & https://defencebay.com/ Currently, we’re working with a client specialising in AI solutions at scale. The platform helps automate and scale ML processes, allowing access regardless of technical prowess. Please note that working on this project requires availability for on-call duty once every six weeks from 5 AM to 5 PM (CEST time zone). Responsibilities Support projects and smaller “paper cuts” for the docs portal Work with OpenAPI spec for REST services (portions of documentation generated from spec) Markdown, MkDocs/Material CI/CD, Git, basic shell/bash scripting Docker, k9s (work with test/deploy pipelines) Some frontend/CSS experience is a plus Required Skills and Experience Proven experience with MkDocs and MkDocs-Material. Experience with other static site generators (e.g., Hugo, Jekyll, Sphinx) is a plus. Proficiency in Python. Familiarity with dependency management tools like Poetry. Experience with scripting to automate tasks, such as managing redirects, generating documentation, and integrating with external systems. Deep understanding of REST API principles and the OpenAPI Specification. Experience with generating API documentation from spec files (e.g., using tools like Swagger or Redoc). Expertise in using Git and GitHub for version control, including pull request workflows. Experience with continuous integration/continuous deployment (CI/CD) pipelines, particularly with GitHub Actions for tasks like linting (Vale) and build processes. Knowledge of modern development best practices, including writing clean, maintainable code, and testing. Experience with web accessibility standards (e.g., WCAG) is a plus, as it's often a component of a quality front-end experience. Desirable Experience (Plus) Strong proficiency in front-end technologies: HTML, CSS, and JavaScript. Proven capability to translate design specifications into precise, pixel-accurate implementations. Understanding of basic security best practices in a development environment—especially when handling credentials, API keys, and sensitive configuration files. Awareness of potential risks in integrating AI tools (e.g., prompt injection, data exposure) is beneficial. Benefits: B2B contract International projects, often at the cutting edge of technology Experienced team - exchange your expertise with other passionate engineers Modern tech stacks Flexible hours Integration meetings

🏢 Summary: Development of LLM-powered applications and data pipelines for a modern insurance platform, integrating multiple data sources in AWS and Snowflake environments. The role focuses on building and improving a domain-specific chatbot using advanced LLM techniques such as RAG, prompt engineering, and feedback loops. It requires close collaboration with cross-functional teams and availability in the PT timezone. 🗂️ Requirements: Commercial experience with TypeScript, Experience building LLM-powered applications, Hands-on experience with AWS, Experience with Snowflake, Experience designing ETL or ELT pipelines, Experience integrating APIs and external data sources, Ability to design data transformations and data-access layers, Fluent English, Availability for meetings in PT timezone 📃 Skills: TypeScript, Snowflake, AWS, LLM, RAG, APIs, ETL, ELT, Chatbots, SQL, Prompting, Evaluation, Orchestration, EventDriven 🏢 Description: We’re Devopsbay - MLOPS, DevOps and AI Specialists. We know how nodes works, how to make the cloud cheaper or adapt AI to boost any area that companies need (any many more). We support our clients with strong engineers on a project basis and are always on the lookout for stellar performers. Our clients are at the cutting edge of modern solutions. We also develop our inhouse products: https://descrb.com/ & https://defencebay.com/ Please note that working within this project means availability for meetings in PT timezone (mainly till 19:00, usually no later than 18:00) and fluent English. About project: It is a modern insurance brokerage and advisory firm that supports fast-growing companies, particularly in the technology, life sciences, and professional services sectors. The organization combines deep risk management expertise with advanced technology and AI-powered tools to deliver more efficient, tailored insurance solutions to its clients. Its mission is to transform the traditional insurance industry, which is often perceived as complex, slow, and not well suited to the needs of modern businesses. Through digital workflows, automation, and a customer-centric approach, the company simplifies insurance processes, accelerates decision-making, and improves transparency across the entire client experience. By partnering with ambitious leaders and innovative organizations, it helps businesses identify, manage, and mitigate risks associated with growth. Beyond providing insurance coverage, the company offers strategic advisory services that enable clients to make confident decisions and scale their businesses with greater security and peace of mind. What you will do : Work with the following technologies and environments: Agentic AI , TypeScript, Snowflake, AWS, LLM-related technologies , data integrations, APIs, ETL/ELT pipelines. Build LLM-powered applications using modern approaches such as retrieval-augmented generation, tool usage, context management, prompt engineering, evaluation, and feedback loops. Work on a chatbot that can learn from user interactions, improve over time, and support users with domain-specific knowledge. Design and implement integrations with multiple internal and external data sources. Prepare reliable data pipelines, transformations, and data-access layers that enable LLM applications to use structured and unstructured data effectively Take ownership of ambiguous problems and drive solutions end-to-end. Communicate with the team, discuss new ideas, and work closely with non-technical users. Work on a dynamic, startup-style project where learning the domain, experimenting, and iterating quickly are important. Nice To Have: Experience with event-driven architectures and workflow orchestration tools. Experience in regulated domains such as insurance, fintech, or healthcare. Familiarity with AWS services and distributed backend infrastructure. Benefits: B2B contract International projects, often at the cutting edge of technology Experienced team - exchange your expertise with other passionate engineers A challenging yet thriving work environment - we push ourselves to be better everyday Modern tech stacks Remote working possibilities Flexible hours

🏢 Summary: The offer is for a Senior DevOps Engineer to support a fintech IT transformation project focused on building secure and scalable AWS cloud infrastructure and CI/CD pipelines. The role involves designing and maintaining production-grade AWS environments, implementing Infrastructure as Code with Terraform, and driving DevOps and DevSecOps best practices. The project leverages modern cloud, container, and automation technologies in a payments technology domain. 🗂️ Requirements: Minimum 5 years of hands-on experience with AWS, Deep knowledge of core AWS services including ECS, EKS, Lambda, EC2, S3, VPC, IAM, RDS, DynamoDB, Experience designing and maintaining production-grade AWS infrastructure, Experience with AWS Cognito and security best practices (IAM, KMS, Secrets Manager), Advanced experience with Terraform and Infrastructure as Code, Experience managing remote Terraform state with S3 and DynamoDB, Strong experience with Ansible for configuration management, Strong knowledge of Linux (RHEL-based systems), Proficiency in Python for automation and AWS integrations, Experience designing and maintaining CI/CD pipelines, Experience with Jenkins, GitLab CI, Azure DevOps or GitHub Actions, Hands-on experience with Docker and Kubernetes (preferably EKS), Experience with monitoring and observability tools, Practical knowledge of SQL and NoSQL databases, Very good knowledge of Git and branching strategies 📃 Skills: AWS, Terraform, EKS, ECS, Lambda, EC2, S3, IAM, RDS, DynamoDB, Cognito, Ansible, Linux, Python, Node.js, Jenkins, GitLab, Azure, GitHub, Docker, Kubernetes, ArgoCD, FluxCD, Grafana, Prometheus, CloudWatch, Loki, Datadog, Splunk, PostgreSQL, MySQL, MongoDB, Git 🏢 Description: Team Connect jest wiodącym polskim dostawcą usług IT typu nearshore i offshore. Od 2008 roku z sukcesem tworzymy i rozwijamy oprogramowanie dla naszych klientów. Jesteśmy również certyfikowanym partnerem Salesforce. Specjalizujemy się w tworzeniu oprogramowania w oparciu o Agile i DevOps. Od etapu analizy po wdrożenie. Tworzymy aplikacje backendowe, frontendowe i mobilne. Dla jednego z naszego Klientów poszukujemy osoby na stanowisko Senior Devops Engineera , który posiada praktyczne doświadczenie w projektowaniu, wdrażaniu i obsłudze infrastruktur chmurowych AWS, automatyzacji procesów oraz tworzeniu bezpiecznych i skalowalnych potoków CI/CD. Lokalizacja: praca hybrydowa z Warszawy Opis: Projekt będzie dotyczył transformacji IT w sektorze fintech, wykorzystującej technologie Java 21/Spring Boot i kładącej duży nacisk na jakość oprogramowania oraz praktyki programistyczne. Projekt dotyczy branży technologii płatności, kształtując sposób, w jaki świat płaci i otrzymuje płatności. Technologia Klienta napędza rozwój milionów firm na 5 kontynentach. Kluczowe technologie: AWS, Terraform (IaC), EKS, CI/CD, Python. Zakres obowiązków: Współpraca z zespołami programistycznymi w celu wdrażania najlepszych praktyk DevOps i DevSecOps w środowiskach produkcyjnych. Aktywny udział i wkład we wszystkich fazach cyklu życia produktu, w tym w fazie odkrywania, dostarczania i operacji. Realizacja wyznaczonych celów, dostosowując się do wszelkich wymagań niezbędnych do osiągnięcia celu. Wymagania: Cloud Platform - AWS: min. 5 lat praktycznego doświadczenia w pracy z AWS. dogłębna znajomość podstawowych usług AWS, w tym: ECS, EKS, Lambda, EC2, S3, EBS, VPC, IAM, CloudWatch, CloudTrail Route 53, API Gateway, EventBridge, SNS, SQS RDS, Aurora PostgreSQL, DynamoDB doświadczenie z AWS Cognito: pule użytkowników, pule tożsamości, klienci aplikacji i procesy uwierzytelniania. solidne zrozumienie najlepszych praktyk bezpieczeństwa AWS: IAM oparty na zasadzie minimalnych uprawnień, KMS, Secrets Manager, certyfikaty ACM. doświadczenie z Route 53: publiczne i prywatne strefy hostowane, zarządzanie DNS oraz integracja usług. znajomość architektur wielo-kontowych, AWS Landing Zones oraz granic uprawnień. sprawdzona umiejętność projektowania i utrzymywania bezpiecznych, skalowalnych infrastruktur AWS klasy produkcyjnej. certyfikat AWS Solutions Architect (Associate/Professional) lub równoważne doświadczenie. Infrastruktura jako kod – Terraform: zaawansowane doświadczenie w pracy z Terraform: projektowanie modułów wielokrotnego użytku z kontrolą wersji. zdalne zarządzanie stanem przy użyciu S3 i DynamoDB. architektury IaC dla wielu środowisk (dev, qa, sta, prod). doświadczenie w zarządzaniu stanem Terraform, radzeniu sobie z odchyleniami oraz refaktoryzacji IaC. znajomość: Checkov, TFLint, terraform-docs w zakresie bezpieczeństwa i jakości kodu. certyfikat Terraform Associate (mile widziany). Zarządzanie konfiguracją i automatyzacja: bogate doświadczenie w pracy z Ansible: tworzenie ról, skryptów, wykazów zasobów oraz gotowych wzorców automatyzacji. integracja z procesami CI/CD oraz środowiskami hybrydowymi. Systemy operacyjne i skrypty: dogłębna znajomość systemu Linux, zwłaszcza systemów opartych na RHEL. doświadczenie w pracy z serwerami bastionowymi i bezpiecznym dostępem SSH. biegła znajomość języka Python: skrypty automatyzacyjne, integracje z AWS (boto3), narzędzia wewnętrzne. doświadczenie w korzystaniu z Node.js do tworzenia skryptów oraz zadań związanych z CI/CD. CI/CD i DevSecOps: doświadczenie w projektowaniu i utrzymywaniu kompleksowych potoków CI/CD. praktyczne doświadczenie w pracy z potokami dla aplikacji backendowych i frontendowych, znajomość narzędzi i platformy: Jenkins, GitLab CI, Azure DevOps, GitHub Actions integracja z: SonarQube do kontroli jakości kodu. narzędzia do skanowania bezpieczeństwa i wdrażania polityk jako kodu (Checkov, Sentinel itp.). zautomatyzowane etapy testowania i walidacji. doświadczenie w pracy z rejestrami kontenerów: Amazon ECR, JFrog Artifactory, Nexus. Containers & Orchestration: bogate doświadczenie w pracy z Dockerem: optymalizacja obrazów, kompilacje wieloetapowe, prywatne repozytoria. dobra praktyczna znajomość Kubernetes, najlepiej EKS. znajomość praktyk i narzędzi GitOps: ArgoCD, FluxCD (mile widziane). certyfikaty CKA / CKAD będą dodatkowym atutem. Observability & Monitoring: praktyczne doświadczenie w korzystaniu z Grafany i Prometheusa do monitorowania infrastruktury oraz środowiska Kubernetes. doświadczenie w pracy z AWS CloudWatch (wskaźniki, logi, alarmy, pulpity nawigacyjne). doświadczenie w pracy z Loki w zakresie scentralizowanej agregacji logów. doświadczenie w pracy z Datadog w zakresie monitorowania infrastruktury, APM i alertów. doświadczenie w pracy z Splunk i Logz.io w zakresie zarządzania logami i ich analizy. znajomość najlepszych praktyk dotyczących alertów, wskaźników SLI/SLO oraz rozwiązywania problemów związanych z incydentami. Bazy danych: praktyczna znajomość baz danych SQL i NoSQL: PostgreSQL, MySQL, MongoDB. doświadczenie w pracy z bazami danych zarządzanymi przez AWS: RDS, Aurora PostgreSQL, DynamoDB. doświadczenie we wspieraniu aplikacji opartych na bazach danych w środowiskach chmurowych. Dodatkowe umiejętności: biegła znajomość systemu Git oraz popularnych strategii tworzenia gałęzi. doświadczenie w zakresie rozwiązań do monitorowania, rejestrowania zdarzeń i powiadamiania. znajomość zasad niezmiennej infrastruktury oraz ciągłego dostarczania. doskonałe umiejętności w zakresie rozwiązywania problemów na poziomie infrastruktury, sieci oraz aplikacji. doskonałe umiejętności w zakresie dokumentacji oraz doświadczenie w przekazywaniu wiedzy. Benefity: Długofalowa współpraca. Pakiet benefitów – Multisport, prywatna opieka medyczna, ubezpieczenie na życie. Budżet szkoleniowy. Bezpłatne lekcje angielskiego. Indywidualne wsparcie ze strony dedykowanego opiekuna firmy.

🏢 Summary: The offer is for a backend-focused AI Engineer role building a modern AI platform for business process automation and multi-agent system integration in a production-grade enterprise environment. The position centers on developing scalable Python-based services, secure API integrations, and cloud-native AI solutions using LLMs and RAG. The role involves designing robust, secure, and scalable architectures deployed on AWS or Azure with containerized infrastructure. 🗂️ Requirements: Extensive experience in backend development with Python in production environments, Hands-on experience with AI Agents, RAG, MCP, or LLM-based solutions, Experience with system integrations and API architecture, Experience with scalable cloud-based applications, Experience with AWS or Azure, Experience with Docker and Kubernetes, Experience designing secure and scalable enterprise solutions, Experience with multi-agent systems and workflow automation, Ability to conduct code reviews and mentor developers, Fluent English and Polish 📃 Skills: Python, LLM, RAG, MCP, AWS, Azure, Docker, Kubernetes, API, Microservices, Cloud, AI, Agents 🏢 Description: Additional information The project focuses on building and developing a modern AI platform supporting business process automation and the integration of intelligent agents with enterprise systems. The team is creating scalable solutions based on Python, cloud technologies, and multi-agent architecture, leveraging technologies such as LLMs, RAG, and advanced workflow automation. A key aspect of the project is designing secure integrations between AI platforms, internal systems, and external APIs within a production-grade environment. The project is delivered in an international technology-driven environment with a strong focus on innovation, high-quality architecture, and the development of cutting-edge AI solutions for a global industrial organization. You’re ideal for this role if you: Have extensive experience in backend development with Python in production environments Have hands-on experience with AI technologies such as AI Agents, RAG, MCP, or LLM-based solutions Understand system integrations, API architecture, and scalable cloud-based applications Have worked with AWS or Azure and containerized environments such as Docker and Kubernetes Are experienced in designing secure and scalable enterprise solutions Have strong problem-solving skills and can proactively remove technical blockers Enjoy working closely with cross-functional teams in an international environment Have experience mentoring developers, conducting code reviews, and promoting engineering best practices Are interested in modern AI architectures, workflow automation, and multi-agent systems Communicate fluently in English and Polish and feel comfortable working in a global setup Your day-to-day responsibilities include:​ Designing and developing scalable backend services and AI-driven integration solutions in Python Building and maintaining APIs, connectors, and middleware between AI platforms and enterprise systems Creating and optimizing multi-agent workflows and intelligent automation processes Collaborating with AI Engineers, Data Engineers, and other technical stakeholders on system architecture and integrations Integrating external AI platforms, internal tools, and cloud services into production environments Working with cloud technologies and containerized infrastructure in AWS or Azure environments Improving the quality, reliability, and performance of AI-powered solutions and LLM-based workflows Conducting code reviews, mentoring team members, and supporting engineering best practices Troubleshooting technical issues, identifying bottlenecks, and driving continuous improvements Contributing to technical documentation, architecture discussions, and innovation initiatives across the team

🏢 Summary: Hands-on ML Engineer role to evolve a computer vision mobile app from prototype to production, improving model accuracy and building scalable ML infrastructure. You will design automated pipelines for adding new species, optimize models for on-device deployment, and extend support to Android. The role focuses on end-to-end ML lifecycle ownership, from training to mobile deployment. 🗂️ Requirements: 5+ years of ML engineering experience, Strong experience with PyTorch, Experience with vision transformers (ViT/timm), Experience with YOLO or Ultralytics, Experience with full ML lifecycle (training, evaluation, export, deployment), Experience deploying models to CoreML or TFLite, Experience building ML pipelines with versioning and experiment tracking, Experience implementing CI/CD for ML workflows, Experience working with small or noisy datasets, Experience designing scalable classification systems, Experience with orchestration tools (Airflow, Prefect, or Dagster) 📃 Skills: Python, PyTorch, ViT, timm, YOLO, Ultralytics, CoreML, TFLite, Airflow, Prefect, Dagster, CI/CD, MediaPipe, Quantization, Pruning, Distillation 🏢 Description: We’re Devopsbay - MLOPS, DevOps and AI Specialists. We know how nodes works, how to make the cloud cheaper or adapt AI to boost any area that companies need (any many more). We support our clients with strong engineers on a project basis and are always on the lookout for stellar performers. Our clients are at the cutting edge of modern solutions. We also develop our inhouse products: https://descrb.com/ & https://defencebay.com/ Our client is building a mobile app that uses computer vision to identify fish species, classify sex, and estimate length from photos. We’ve proven the concept — species classification at 87.6% accuracy, a length regression model with 73% improvement over baseline, and CoreML export running on iOS. Now we need someone to take this from working prototype to production-grade ML system. The founder has built the initial models and pipeline in Python, and your job is to improve model accuracy, build the infrastructure to support continuous improvement, and extend deployment to Android. This is a hands-on, build-it-yourself role — not a management position. What You’ll Own Design and build a repeatable, scalable process for adding new fish species to the classifier. Today, adding a species involves manual image scraping, hand-curated CSVs, and ad hoc retraining. We need a system where a new species can go from “we want to support this” to “it’s live on device” with minimal manual effort. What We’re Looking For 5+ years of experience in ML engineering, with meaningful time spent on both model development and production infrastructure. Specifically: Strong PyTorch experience, ideally with vision transformers (ViT/timm) and object detection (YOLO/ultralytics) Familiarity with the full model lifecycle — training, evaluation, export, and on-device deployment Hands-on experience deploying models to mobile (CoreML and/or TFLite); you don’t need to be an iOS/Android app developer, but you need to produce optimized model artifacts that mobile engineers can integrate Experience building ML pipelines with proper versioning, experiment tracking, and CI/CD Comfort working with small, noisy datasets and knowing how to get the most out of limited labeled data Experience designing classification systems that scale — adding new classes without full retraining or accuracy regression Familiarity with at least one orchestration tool (Airflow, Prefect, Dagster) Self-directed — you’ll be working with a small team and need to make pragmatic architecture decisions without a lot of oversight Nice to Have Experience with MediaPipe or similar pose/landmark detection frameworks Background in ecological or biological image classification Experience with on-device A/B testing frameworks Familiarity with edge inference optimization (quantization, pruning, distillation) Experience with few-shot learning or other techniques for bootstrapping new classes with limited data

🏢 Summary: Senior DevSecOps Engineer role focused on designing, implementing, and scaling secure, enterprise-grade cloud and DevSecOps foundations in a fast-growing global environment. The position emphasizes AWS infrastructure, Terraform-based IaC, CI/CD collaboration, observability, and security governance with high ownership and architectural responsibility. The role requires driving long-term security, scalability, and operational excellence across teams and regions. 🗂️ Requirements: 10+ years experience in DevOps, DevSecOps, or Security Engineering, Strong hands-on experience with AWS infrastructure and security, Strong experience with Terraform for infrastructure-as-code, Experience designing and managing CI/CD pipelines, Experience with observability and monitoring platforms, Solid knowledge of cloud security, IAM, networking, and core AWS services, Experience implementing security controls and GRC practices, Experience with IT operations and SaaS access management, Ability to design scalable, auditable, and secure architectures, Ability to drive security and infrastructure initiatives independently 📃 Skills: AWS, Terraform, CircleCI, Datadog, IAM, CI/CD, GRC, SaaS, Networking, Observability 🏢 Description: About Moove Moove is building the world’s largest fleet and best-in-class technologies to power mobility platforms. Our flagship Drive-to-Own (DTO) product democratises access to vehicle ownership with a revolutionary revenue-based financing model, enabling underserved mobility entrepreneurs to thrive. Our global growth has been fuelled by our partnership with Uber and backed by leading investors and lenders, including Uber, Mubadala, BlackRock, and many others. Today, Moove operates the world's largest manned & autonomous ride-hail fleet, with 38k+ vehicles across 29 cities, 13 countries and 6 continents enabled by 2.1k+ employees – Moove continues to expand through strategic partnerships with industry leaders like Uber. We’re transforming mobility to be safer, more efficient, and accessible to all, while creating economic opportunities and supporting skills development in the mobility sector. About the Role We are a fast-growing scale-up evolving into a globally operating, enterprise-grade organization . As part of this transition, we are seeking a Senior DevSecOps Engineer who can help us design, implement, and scale security and operational foundations that will support the business for years to come.This is a senior, hands-on role with broad scope and high ownership. You will operate in an environment where not everything is fully defined yet - but where the expectation is to bring clarity, structure, and durable solutions rather than wait for direction.We are looking for someone with an architect mindset : a professional who thinks in systems, values correctness and consistency, and is deeply committed to long-term improvements. This is not a role for someone who optimizes for speed at the expense of quality. What You’ll be Doing Act as a senior technical owner for DevSecOps and cloud security as the organization scales toward enterprise standards. Operate effectively with a high degree of ambiguity, proactively shaping direction rather than executing predefined tasks. Design solutions that are scalable, auditable, and sustainable across multiple teams and regions. Maintain a strong bias toward quality, detail, and correctness in architecture, implementation, and documentation. Think beyond immediate delivery and continuously improve foundations, tooling, and processes. Core Responsibilities: Architect, implement, and continuously improve cloud security and DevSecOps practices across the organization. Design and maintain secure, scalable AWS infrastructure using Terraform with a strong emphasis on best practices and maintainability. Collaborate closely with engineering teams on CI/CD, code-related workflows, and delivery practices. Own and evolve monitoring, alerting, and observability using Datadog . Lead the design and implementation of foundational security capabilities, including: Identity and access management Secrets and key management Network security and segmentation Logging, auditing, and incident readiness Drive security governance and GRC-related initiatives . Provide mentorship and set engineering standards through example, reviews, and documentation. Collaborate with Engineering and IT Operations teams to ensure systems are secure, resilient, and operationally sound. What You will need for this position 10+ years of professional experience in DevOps, DevSecOps, Security Engineering, or related roles. Proven track record of successfully delivering meaningful security and infrastructure improvements in complex environments. Strong hands-on experience with: AWS (security, networking, IAM, and core services) Terraform (modular, scalable, and secure infrastructure-as-code) CI/CD pipelines (CircleCI or comparable tools) Datadog or similar observability platforms Solid understanding of security and GRC best practices, including risk management, controls, and audit concepts. Practical experience with day-to-day IT operations, including SaaS tooling, access management, operational workflows, and application of IT best practices in a growing organization. Demonstrated ability to work independently, prioritize effectively, and drive initiatives from idea to execution. Strong attention to detail, documentation quality, and operational rigor. Clear communicator who can explain complex technical and security concepts to both technical and non-technical audiences. Nice to have Experience with compliance frameworks. Key Metrics Success in this role is measured by tangible improvements in security, operational maturity, and scalability , including: Security posture Reduction in high- and critical-risk findings Consistent implementation of security controls and best practices DevSecOps maturity Increased standardization and reliability of infrastructure and security patterns Reduced manual work and configuration drift through durable automation GRC & audit readiness Ability to meet audit and enterprise customer requirements with minimal friction High-quality, repeatable security documentation and evidence Operational quality Clear, actionable observability and alerting Fewer security and operational issues caused by process or configuration gaps Long-term impact Delivery of scalable, well-architected improvements adopted across teams Trust established as a senior technical owner and advisor Who You'll Be Working with: Directly reporting to our Head of Enterprise Architecture, and closely working with our PED - Technology Operations Team. About the team Our team is collaborative, positive, curious, and engaged. We think fast, work smart, laugh often, and are looking for like-minded people to join us in our mission to disrupt vehicle ownership and make financial freedom within reach. Moove is strongly committed to diversity within its community. The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. Pre-hiring Notice: Moove relies on the accuracy of information contained in employment applications, as well as the accuracy of other data presented throughout the hiring process and during employment. Any misrepresentations, falsifications, or material omissions in any information or data provided by an applicant may result in the applicant being excluded from further consideration for employment or if an individual has already been hired, termination of employment. EEO Statement: Moove is an equal opportunity employer and does not discriminate on the basis of gender, race, sexual orientation, marital status, religion, political affiliation or any other protected characteristic.

🏢 Summary: Remote backend engineering role focused on building secure, scalable backend services and APIs using Python and Java within a cloud-native, security-driven environment. The position involves developing microservices, managing Kubernetes-based deployments, and integrating with AWS and Splunk for security analytics and monitoring. The engineer will work closely with security and frontend teams in an Agile setup. 🗂️ Requirements: Minimum 3 years of backend engineering experience, Proficiency in Python 3, Proficiency in Java, Experience with RESTful APIs, Experience with microservices architectures, Hands-on experience with AWS (DynamoDB, IAM, Lambda, API Gateway), Strong knowledge of Redis and high-availability configurations, Experience with Docker and Docker Compose, Practical experience with Kubernetes, Experience with Helm, Experience with Splunk Enterprise data ingestion and analytics, Knowledge of HTTP Event Collector configuration, Experience with authentication and IAM, Experience integrating with Identity Providers, Bachelor’s degree in Computer Science, Engineering or equivalent experience 📃 Skills: Python, Java, REST, Microservices, AWS, DynamoDB, IAM, Lambda, APIGateway, Redis, Docker, Kubernetes, Helm, Splunk, SAML, SSO, HTTP, Webhooks, Protobuf, WebSockets 🏢 Description: Location: 100% remote Tasks Design, develop, and maintain scalable backend services and APIs Build secure, high-performance backend systems using Python 3 and Java Implement RESTful APIs and microservices architectures Implement and manage secure authentication flows using SAML 2.0 and SSO Integrate backend services with frontend components and collaborate with React developers Configure and maintain Splunk Enterprise integrations for security event monitoring Build and maintain Splunk dashboards for threat discovery and investigation Collaborate with security teams on Cisco Secure Firewall and Secure Network Analytics integrations Manage containerized deployments using Docker, Docker Compose, and Kubernetes Administer Kubernetes clusters including deployment, scaling, and Helm chart management Optimize Redis caching strategies including session management and pub/sub messaging Develop and maintain AWS DynamoDB data models and access patterns Configure and manage AWS IAM roles and security policies Implement serverless solutions using AWS Lambda and API Gateway Contribute to endpoint security analytics pipelines using Cisco AnyConnect NVM and CESA Configure NVM Collector and Splunk Add-Ons for endpoint analytics Participate in code reviews, architectural discussions, and technical documentation Work in an Agile/Scrum development environment Requirements At least 3 years of backend engineering experience Proficiency in Python 3 and Java Experience with RESTful APIs and microservices architectures Hands-on experience with AWS including DynamoDB, IAM, Lambda, and API Gateway Strong knowledge of Redis including high-availability cluster configurations Experience with Docker and Docker Compose for containerized development Practical experience with Kubernetes and Helm Experience with Splunk Enterprise data ingestion and analytics Knowledge of HTTP Event Collector configuration and webhook integrations Hands-on experience with security topics (IAM, auth) is highly desirable Experience integrating with Identity Providers and Active Directory attribute mapping Experience with Protobuf and WebSockets is an advantage Experience with Duo Network Gateway and secure access to on-premises resources is a plus Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience Strong problem-solving skills and ability to work in a fast-paced environment Offer Multisport card Private healthcare Access to an e‑learning platform Group life insurance

🏢 Summary: The offer is for a DevOps Engineer to build and operate scalable, secure AWS infrastructure for a cloud-native AI Talent Intelligence Platform. The role focuses on production-grade infrastructure, CI/CD automation, observability, security, cost optimization, and ML/AI workload support. It involves full ownership of AWS environments across development and production with strong emphasis on reliability and compliance. 🗂️ Requirements: 5+ years of production infrastructure experience, 3+ years of hands-on AWS experience, Strong experience with AWS services: RDS Postgres, VPC, IAM, ECS or EKS, ALB/NLB, Route53, S3, CloudFront, CloudWatch, Secrets Manager, Advanced Terraform usage: modules, remote state, drift detection, multi-environment setups, Experience building and maintaining CI/CD pipelines (GitHub Actions or equivalent), Proficiency with Linux and containerization, Experience implementing observability: metrics, logs, traces, alerting, On-call and incident management experience, PostgreSQL operations knowledge: backups, migrations, performance tuning, Security best practices: IAM policies, secret management, encryption, AWS cost monitoring and optimization, English proficiency Intermediate+ or higher 📃 Skills: AWS, RDS, PostgreSQL, EC2, ECS, EKS, VPC, IAM, Route53, S3, CloudFront, CloudWatch, SecretsManager, ACM, SES, Terraform, GitHubActions, Linux, Docker, Grafana, Datadog, CI/CD, ALB, NLB, TLS 🏢 Description: Andersen is hiring a DevOps Engineer in the EU for a project building cloud-native AI platforms and ensuring scalable, secure, and reliable infrastructure. The customer is an international company focused on delivering innovative digital solutions and technology-driven services. The organization supports businesses in improving operational efficiency, streamlining processes, and accelerating digital transformation initiatives. By leveraging modern technologies and industry best practices, the company develops scalable and secure solutions tailored to evolving business needs. The customer operates in a dynamic environment, emphasizing innovation, collaboration, and the continuous enhancement of products and services to create long-term value for its clients. The project is focused on developing a cloud-native Talent Intelligence Platform powered by AI and machine learning technologies. It includes building scalable AWS-based infrastructure, supporting intelligent search and ranking capabilities, and ensuring secure, reliable, and observable platform operations. Responsibilities: Owning AWS infrastructure across dev and prod — RDS (Postgres), EC2/ECS/EKS workloads, VPC, IAM, Route53, S3, CloudFront, Secrets Manager, ACM, SES, CloudWatch. Keeping dev and prod in lockstep — same Terraform modules, same patterns, real environment parity. Running CI/CD — GitHub Actions pipelines across several service repos (backend, frontend, AI/ML, gateway, billing). Trunk-based, feature-flagged, main always deployable. Codifying infrastructure — Terraform for everything that touches AWS. No click-ops. Managing observability — metrics, logs, traces, alerting. CloudWatch + Grafana/Datadog (your call, with budget). SLOs that matter. Participating in incident response — on the rotation. Writing runbooks. Leading blameless postmortems. Managing cost control — monthly bill review, right-sizing, Savings Plans / RIs, S3 lifecycle, RDS tuning. Catching anomalies before finance does. Ensuring security & compliance — IAM least-privilege, secrets rotation, vulnerability scanning, GDPR-aligned data handling with EU-resident third-party providers, backup/DR testing. Supporting ML/AI infrastructure — model serving latency budgets, embedding storage, GPU/CPU tradeoffs, A/B infrastructure for ranking experiments. Managing database operations — RDS upgrades, parameter tuning, backward-compatible migrations, read replicas, PITR. Must-have: Experience running production infrastructure for 5+ years. Experience working with AWS for 3+ years. Hands-on with: RDS Postgres, VPC networking, IAM, ECS or EKS, ALB/NLB, Route53, S3, CloudFront, CloudWatch, Secrets Manager. Terraform in anger — modules, remote state, drift detection, multi-environment. CI/CD — GitHub Actions or equivalent. Linux + containers — Docker, image hygiene, sensible base images, multi-stage builds. Observability — metrics, logs, traces, and alerting. Incident command — on-call experience, leading incidents, writing postmortems. PostgreSQL operations — backups, migrations, query performance basics, RDS quirks. Security fundamentals — IAM policy writing, secret management, TLS, encrypted-at-rest by default. Cost awareness — monitoring and optimizing AWS infrastructure costs. Level of English – from Intermediate+ and above. Nice to haves: Experience with Keycloak in production environments. Experience with Vespa, Elasticsearch, OpenSearch, or other search infrastructure. Experience with AWS Bedrock or other managed AI tooling. Experience with ML serving using SageMaker, Bedrock, or self-hosted GPU inference. Experience with GDPR compliance and EU data residency requirements. Experience with Helm, Kustomize, and ArgoCD. FinOps mindset — tagging strategy, showback, and anomaly detection. Reasons why this job would be interesting to you: Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc.. The opportunity to change the project and/or develop expertise in an interesting business domain. Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee. The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities. Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated. Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies). Certification compensation (AWS, PMP, etc). Referral program. Private health insurance and compensation for sports activities. Your personal data is protected in accordance with GDPR regulations. Learn more: https://andersenlab.com/privacy-policy/pl Join us! https://people.andersenlab.com/

🏢 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: The offer is for an experienced DevOps Engineer to design, implement and maintain cloud infrastructure in AWS, focusing on automation, CI/CD and high availability of production systems. The role involves developing Infrastructure as Code, managing containerized environments and supporting system performance, security and reliability in a financial sector project. 🗂️ Requirements: Minimum 5 years of experience as DevOps Engineer, Cloud Engineer or similar, Strong knowledge of AWS, Hands-on experience with Terraform, Experience with Linux administration, Experience with Docker and Kubernetes, Experience with CI/CD tools such as Jenkins or GitLab CI, Scripting skills in Python or Bash, Very good command of English 📃 Skills: AWS, Terraform, Linux, Docker, Kubernetes, Jenkins, GitLab, Python, Bash, CI/CD, Prometheus, Grafana, ELK 🏢 Description: Nasz Klient to firma z branży finansowej, rozwijająca i utrzymująca nowoczesne rozwiązania technologiczne wspierające kluczowe procesy biznesowe oraz obsługę klientów. Projekt koncentruje się na rozwoju środowisk chmurowych, automatyzacji procesów wdrożeniowych oraz zapewnieniu wysokiej dostępności i bezpieczeństwa systemów wykorzystywanych w organizacji. Szukamy doświadczonej osoby na stanowisko DevOps Engineer, która będzie wspierać rozwój infrastruktury, optymalizację procesów oraz wdrażanie nowoczesnych praktyk w obszarze automatyzacji i utrzymania środowisk. 📍 TRYB PRACY: 100% zdalnie 🧑‍💻 CZYM BĘDZIESZ SIĘ ZAJMOWAĆ? Projektowaniem, wdrażaniem i utrzymywaniem środowisk chmurowych wspierających kluczowe systemy biznesowe Automatyzacją procesów wdrożeniowych oraz rozwijaniem procesów CI/CD Tworzeniem i utrzymywaniem rozwiązań IaC z wykorzystaniem Terraform Zarządzaniem konteneryzacją i orkiestracją aplikacji w środowisku Docker oraz Kubernetes Monitorowaniem wydajności, dostępności i bezpieczeństwa systemów produkcyjnych Współpracą z zespołami developerskimi przy wdrażaniu i optymalizacji rozwiązań chmurowych 🔍 CZEGO OD CIEBIE OCZEKUJEMY? Must have: Minimum 5 lat doświadczenia na stanowisku DevOps Engineer, Cloud Engineer lub pokrewnym Bardzo dobra znajomość AWS Doświadczenie w pracy z Terraform Znajomość Linux oraz zagadnień administracyjnych związanych z utrzymaniem środowisk Doświadczenie z Docker oraz Kubernetes Znajomość narzędzi Jenkins , GitLab CI lub podobnych rozwiązań CI/CD Umiejętność tworzenia skryptów w Python lub Bash Bardzo dobra znajomość języka angielskiego Nice to have: Doświadczenie w sektorze finansowym, bankowym lub ubezpieczeniowym Znajomość rozwiązań monitorujących, takich jak Prometheus , Grafana lub ELK Stack Doświadczenie z rozwiązaniami security i compliance w środowiskach chmurowych Certyfikaty AWS 🤝 DLACZEGO WARTO? 🚀 Realny wpływ na rozwój środowiska chmurowego oraz wdrażane rozwiązania infrastrukturalne 🌍 Współpraca z doświadczonym zespołem specjalistów i architektów 📈 Możliwość zdobywania doświadczenia w obszarze chmury, automatyzacji i nowoczesnych technologii 🛠️ Projekt wykorzystujący rozwiązania oparte o AWS , Terraform , Kubernetes , Prometheus i Grafana Dziękujemy za wszystkie zgłoszenia! Skontaktujemy się z wybranymi osobami. TQLO Sp. z o.o. – Agencja Zatrudnienia (nr KRAZ 33580)