Your role at Dynatrace - You will create automations for the continuous integration of the Dynatrace platform. - You will operate delivery-critical services hosted on AWS EKS. - Together with the team, you will iteratively improve our offering for internal developers to boost engineering productivity. - You will make extensive use of Kubernetes and cloud-native technologies like Harbor and SigStore. - You will be at the forefront of providing the whole GitHub experience to other developers, from repository as code to self-hosted GitHub runners. - You will make use of AI tools like CoPilot and Claude. What will help you succeed - 3+ years of proven knowledge in Kubernetes - You are versatile with cloud providers (ideally AWS) and setting up infrastructure as code (e.g., Crossplane, Terraform, CloudFormation) - Understanding CI/CD, ideally backed by experience with Jenkins or GitHub Actions - Automation Mindset: Focus on automating workflows and processes to streamline operations - Strong analytical and problem-solving skills - Excellent communication and interpersonal skills Why you will love being a Dynatracer - Dynatrace is a leader in unified observability and security. - We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. - Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. - The Dynatrace platform uses cutting-edge technologies, including our own Davis hypermodal AI, to help our customers modernize and automate cloud operations, deliver software faster and more securely, and enable flawless digital experiences. - Over 50% of the Fortune 100 companies are current customers of Dynatrace. Compensation and Rewards - We offer attractive compensation packages and stock purchase options with numerous benefits and advantages. - Due to legal reasons, we are obliged to list a salary range for this position, which is €61,000 up to €76,000 gross per year based on full-time employment (38.5 h/week). We’ve listed the salary range for transparency, but if your experience and skills bring unique value, we’d still love to hear from you - please apply even if you’re outside the range. Equal Employment OpportunityDynatrace provides equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected characteristic. We actively foster an inclusive workplace that celebrates differences and promotes accessibility, collaboration, and growth for all.

• Mantenimiento de pipelines de Azure • Mantenimiento de apps tanto de ios como de android • Creación de recursos en azure • Gestion de apps tanto de iphone como de android (play store, appStore)

Role Description The Managed Services team is a newly formed squad within the Databases department. It owns and operates shared, production-critical infrastructure that powers Grafana Cloud’s next-generation database products (Mimir, Loki, and Tempo). Today, this includes operating 100+ WarpStream clusters across multiple cloud providers and regions, with continued growth anticipated for the future. WarpStream acts as the streaming backbone for ingestion and read/write decoupling across databases. It sits directly on the hot path for metrics, logs, and traces, handling high-throughput, multi-consumer workloads at massive scale. In addition to streaming infrastructure, the team works closely with high-volume analytical and storage systems that power query-heavy and aggregation-heavy workloads, where latency, compression behavior, storage layout, and scaling characteristics matter deeply. What You’ll Be Doing - Operating and evolving 100+ multi-cloud streaming clusters and related database infrastructure - Diagnosing and eliminating cross-layer failure modes (e.g., object storage latency, noisy neighbors, control-plane bottlenecks, query performance regressions, etc.) - Designing safe upgrade and rollout strategies at scale - Improving observability, automation, and operational ergonomics - Partnering closely with database and platform teams to ensure safe scaling, partitioning, consumer fan-out, and query performance - Working directly with distributed systems behavior, Kubernetes scheduling dynamics, storage engines, compression trade-offs, etc. - Serving as a primary escalation point and on-call for relevant incidents - Owning the relationship with all system vendors, including WarpStream Labs and others What Makes You a Great Fit - Regular 1:1s with your manager and close collaboration with teammates across regions - Reviewing and defining SLOs for shared database infrastructure, proactively reducing error budgets through improvements to monitoring, automation, scaling strategies, and system design - Improving the diagnosability of core streaming and database systems in production, where possible - Implementing solutions that ensure reliability, scalability, and performance of high-throughput, multi-cloud infrastructure - Developing fault-tolerant patterns that account for distributed system realities such as storage latency, partition imbalance, noisy neighbors, and control-plane dependencies - Planning and executing safe upgrades and rollouts across dozens of production clusters - Collaborating with database and platform engineering leaders to influence architecture, roadmap priorities, and long-term strategy - Participating in PR review and contributing to design documents, automation, tooling, and code improvements that reduce operational risk - Sharing best practices and distributed systems knowledge with partner teams - Participating in incident response, from investigation through resolution and post-incident reviews (PIR) Requirements - 6+ years of engineering experience, including meaningful time in SRE, platform engineering, production engineering, infrastructure engineering, or distributed systems roles - Experience operating distributed systems in production (e.g., streaming systems, analytical databases, large-scale storage backends). Examples of these include Kafka, Redpanda, WarpStream, Postgres, ClickHouse, Snowflake, or Cassandra - Strong Kubernetes experience in AWS, GCP, or Azure, and familiarity with infrastructure-as-code tooling (Helm, Terraform, Jsonnet, etc.) - Solid understanding of distributed systems design and large-scale system trade-offs - Proficiency in at least one programming language (Go preferred, but not required) - Working knowledge of Linux internals, networking, cloud storage, and performance/scaling behavior - Experience participating in blameless incident response and writing high-quality post-incident reviews - Clear communicator who can collaborate across teams and work autonomously - Curious, pragmatic, action-oriented, and kind (this is important!) Compensation & Rewards In the United States, the Base compensation range for this role is USD 154,445 - USD 185,334. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. Why You’ll Thrive at Grafana Labs - 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose - Scaling Organization - Tackle meaningful work in a high-growth, ever-evolving environment - Transparent Communication - Expect open decision-making and regular company-wide updates - Innovation-Driven - Autonomy and support to ship great work and try new things - Open Source Roots - Built on community-driven values that shape how we work - Empowered Teams - High trust, low ego culture that values outcomes over optics - Career Growth Pathways - Defined opportunities to grow and develop your career - Approachable Leadership - Transparent execs who are involved, visible, and human - Passionate People - Join a team of smart, supportive folks who care deeply about what they do - In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it - Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect Equal Opportunity Employer We will recruit, train, compensate and promote regardless of race, religion, color, national origin, gender, disability, age, veteran status, and all the other fascinating characteristics that make us different and unique. We believe that equality and diversity builds a strong organization and we’re working hard to make sure that’s the foundation of our organization as we grow.

Role Description We are seeking an AI Developer with strong expertise in Generative AI, Large Language Models (LLMs), and prompt engineering to design, build, and optimize intelligent systems. The ideal candidate will have hands-on experience with multi-agent architectures, LLM orchestration, and production-grade AI deployments. Key Responsibilities - Design, develop, and deploy applications powered by LLMs and generative AI models - Engineer, test, and optimize prompts for performance, accuracy, and reliability - Build and manage multi-agent systems for complex task orchestration - Integrate AI models with APIs, databases, and external tools - Implement retrieval-augmented generation (RAG) pipelines - Fine-tune and evaluate models using domain-specific datasets - Monitor model outputs, ensure alignment, and reduce hallucinations - Collaborate with product, data, and engineering teams to deliver AI-driven features Qualifications - Strong programming skills in Python (preferred) or similar languages - Deep understanding of prompt engineering techniques and patterns - Experience working with OpenAI, open-source LLMs, or similar platforms - Familiarity with vector databases and embeddings (e.g., Pinecone, FAISS) - Knowledge of multi-agent architectures and orchestration strategies - Understanding of AI evaluation metrics and model performance tuning Preferred Qualifications - Experience with fine-tuning LLMs or training custom models - Knowledge of cloud platforms (AWS, GCP, Azure) - Exposure to conversational AI, chatbots, or copilots - Understanding of AI safety, guardrails, and governance