We put AI firstWe're looking for a Principal Generative AI Engineer to build AI systems that connect development workflows with production observability. You'll design and ship agentic tooling that helps engineers understand code, assess the impact of changes before they hit production, and act on real runtime signals. Your role at DynatraceWe are looking for a visionary, technically excellent engineer who is ready to design and ship production-grade agentic AI systems that bridge the gap between code context and runtime signals. You should thrive on a foundation of freedom, feedback, and responsibility, bringing a startup-like drive backed by the reach of a global platform. - Design, build, and ship agentic AI systems and tooling that helps engineers understand code, assess the impact of changes before they hit production, and act on real runtime signals. - Build production LLM systems end to end, managing prompting, tool calling, retrieval, memory management, and the agent loops that tie them together. - Define the evaluation strategies, metrics, and datasets that make agent quality measurable, ensuring we ship on evidence and catch regressions across model and prompt changes. - Connect development workflows with production observability, turning code context and runtime signals into reliable, actionable insight, and collaborate with product, design, and platform teams to identify developer problems. - Set technical strategy and architectural direction for the team's AI systems, mentor engineers across the organization, and take full ownership of systems using Dynatrace to monitor and optimize them. What will help you succeedYou are a seasoned technical leader with a strong software engineering foundation and proven hands-on experience deploying complex LLM applications. You possess the engineering judgment to navigate ambiguous, fast-moving spaces and set clear architectural direction for your team. - Degree in Software Engineering or equivalent practical experience in software development, combined with a track record of technical leadership and the judgment to set direction in an ambiguous, fast-moving space. - Extensive experience shipping production systems that use LLMs, including prompting, tool calling, evaluation, and iteration. - A strong foundation in at least one of: developer tooling (IDEs, compilers, static analysis, code intelligence), AI/ML engineering, or large-scale distributed systems. - Hands-on experience with agentic patterns, specifically planning, tool use, retrieval, and memory management. - The ability to evaluate and critique AI-generated output, understanding why a model is wrong, not just that it is, with familiarity with observability and the Dynatrace platform as a strong advantage. 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. - You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically. - Over 50% of the Fortune 100 companies are current customers of Dynatrace. Compensation and RewardsThe base salary range for this role is $146K - $220K. When determining your salary, we consider your experience, skills, education, and work location. Our total compensation package includes unlimited personal time off, an employee stock purchase plan, and a reward system. We also offer medical/dental benefits and a company-matched 401(k) plan for retirement. 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.

Title: Lead AI Engineer Location: Utrecht Utrecht NL Job Description: We are AI builders Since 2018, Enjins has done one thing: ship AI that works in production. From Utrecht and Berlin, we build machine learning systems, data infrastructure, and agentic AI layers for European tech companies, with a deliberate focus on climate and energy, where we believe the biggest technological shift of our generation should meet its most critical challenge. We embed directly with the engineering teams of high-growth scale-ups like Crisp, PlanBlue, NextSense, and Groendus. We take ownership of the full technical lifecycle: from first architecture decision to a production-grade system running inside our partner's infrastructure, long after go-live. The role As Lead AI Engineer, you are the technical owner of client engagements. You architect the solution, ship it to production, and make sure it still performs a year later. Alongside the other Leads, you shape the engineering team and the way we build. In practice: - Design AI roadmaps with client leadership and own them through to production - Set and uphold Data Platform and MLOps standards across your client portfolio, so systems stay healthy after handover - Mentor engineers and weigh in on hiring, team growth, and accounts - Push our engineering practice forward, including how we use agentic coding workflows to build faster without compromising reliability. We test, document, and share what works, so the whole team levels up - Elevate our product mindset to ensure we build the right things, not just more things Why a Lead role here, not somewhere else You'll work across more stacks, clouds, and frontier frameworks in a year than most engineers see in five, with the collective knowledge of the whole team behind you, not the isolation of freelance work. And because our clients build grid software, energy forecasting, and climate infrastructure, you develop real domain expertise in energy and climate systems on top of production-grade AI engineering. In your first months you'll join a client project alongside an experienced Enjins engineer, supported by a dedicated coach. Within half a year, you own the technical roadmap of at least one engagement, mentor engineers, and have a recognised voice in our Asset strategy. Requirements What matters most: you think in systems, own outcomes end-to-end, and grow the people around you. - 5+ years building and scaling AI solutions in production environments - Deep expertise in Python, SQL, and Git; hands-on with containerisation (Docker, Kubernetes) and ETL/ELT orchestration - Mastery of at least one major cloud platform (AWS, Azure, GCP) and experience leading MLOps/LLMOps architectures - Proven experience taking LLM-based or agentic systems to production - Experience mentoring engineers, overseeing delivery, and managing client accounts - You can translate technical complexity into clear decisions for non-technical stakeholders - Fluent in English and eligible to work in the Netherlands Benefits We publish our salary ranges and keep terms straightforward. No surprises. Compensation - €5,500 - €7,250 gross per month (excl. holiday allowance, pension, bonus, equity, and AI-Leap benefits) - Annual performance bonus of 1.5 months' salary - Equity participation (VSOP) Growth - AI-Leap: our structured development programme with a dedicated certification budget and a specialised track for Leads - 1-on-1 mentoring with our founders and external coaching to close your specific gaps Team & culture - Office on the Oudegracht in Utrecht (note: not yet fully accessible for individuals with physical disabilities); hybrid setup - 28 vacation days, flexible across 3 national holidays - Monthly team events and the annual two-day Enjins Summer Summit on AI × Climate - OV-First travel policy, fully covered; meat-free catering - Apple MacBook Pro and the tools you need

• Lead engineering delivery for agentic AI capabilities for GTM stakeholders across its technology stack (Salesforce, Slack, 3rd party apps) and In-House Platforms • Design and build LLM-powered workflows, autonomous agents, multi-agent systems and AI-enhanced integrations using Agentcore, Slack, MCPs, Langchain • Define scalable enterprise AI architecture patterns including model routing, orchestration, memory management and governance strategies • Design and optimize Retrieval Augmented Generation (RAG) systems, semantic search pipelines, vector retrieval strategies and enterprise knowledge grounding frameworks • Build and maintain Apex, Lightning Web Components, Salesforce Platform Events, and Agentforce agent actions • Implement AI evaluation frameworks including prompt quality benchmarking, hallucination reduction and model performance monitoring • Mentor senior and mid-level engineers; conduct code reviews and enforce AI engineering standards • Define error handling, fallback strategies, and graceful degradation patterns for non-deterministic AI systems • Retire legacy integrations and replace them with modern, agentic, event-driven patterns • Champion security-first AI engineering: input validation, output sanitization, and prompt injection hardening • Architect and implement CI/CD pipelines, deployment automation, and platform observability • Embrace Agentic AI and LLM-powered tooling as a core part of your engineering practice • Stay current with rapidly evolving AI/ML technologies and apply them pragmatically to GTM systems • Champion automation-first thinking — if it can be agentic, make it agentic • Build internal tools and apps to streamline data access and GTM decision-making • Implement data governance and monitoring frameworks to enhance GTM system quality • Evaluate vendors and AI platforms with a strategic build vs. buy mindset • Identify and automate manual processes to increase organizational leverage

• Build and scale AI systems: Design, implement, and optimize core components of our agentic AI architecture with a focus on performance and reliability • Develop agentic workflows: Build on multi-agent systems using LLMs, orchestration frameworks (LangGraph), RAG, and context engineering • Ship advanced AI features: Develop innovative capabilities such as layout optimization, structured reasoning flows, and multimodal workflows • Contribute to product evolution: Collaborate closely with product and engineering teams to shape features through experimentation and rapid iteration • Drive continuous improvement: Help refine best practices for evaluation, deployment, monitoring, and scaling of AI systems in production