Applied AI Engineer

<div> <p data-pm-slice="1 1 []"><strong>This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Applied AI Engineer based in Netherlands.</strong></p> <p>As an Applied AI Engineer, you will play a pivotal role in designing and building the next generation of intelligent, agentic systems.<br>You will develop the core infrastructure that enables AI agents to manage context, use tools, coordinate tasks, and continuously improve their performance.<br>Working at the intersection of advanced AI research and practical software engineering, you will transform complex operational workflows into reliable, scalable production solutions.<br>You will establish robust evaluation, testing, and observability frameworks to ensure AI-powered systems deliver predictable and measurable results.<br>You will also explore innovative ways to integrate coding agents and specialized subagents into software development processes.<br>Collaborating closely with product and operational teams, you will identify high-impact automation opportunities and translate them into effective technical solutions.<br>As an early core member of the engineering team, you will have significant influence over architectural decisions, technical standards, and the long-term AI strategy.</p> </div><br><strong>Accountabilities</strong><br><div> <p data-pm-slice="1 3 []">In this role, you will design and implement the technical foundations of agentic systems while driving the adoption of AI-powered engineering workflows. Your responsibilities will include:</p> <ul data-spread="false"> <li> <p>Design and build essential components of agentic systems, including memory, context management, tool-calling capabilities, orchestration mechanisms, and feedback loops.</p> </li> <li> <p>Develop reusable AI infrastructure that enables new workflows to be introduced quickly, consistently, and with predictable reliability.</p> </li> <li> <p>Build comprehensive evaluation frameworks to measure agent performance, identify failure points, and understand the factors behind successful outcomes.</p> </li> <li> <p>Integrate testing, tracing, debugging, and evaluation into the software engineering lifecycle as fundamental practices.</p> </li> <li> <p>Develop systems and validation processes that allow agentic workflows to be thoroughly assessed before production deployment.</p> </li> <li> <p>Advance the use of large language models (LLMs) in software development by creating sophisticated AI-assisted engineering workflows.</p> </li> <li> <p>Build workflows where coding agents and specialized subagents can explore code repositories, implement changes, review architecture, validate conventions, run evaluations, and iterate with minimal human intervention.</p> </li> <li> <p>Actively use agentic engineering tools and workflows in daily development activities.</p> </li> <li> <p>Design architectures that enable specialized AI agents, tools, deterministic software, and human expertise to work together effectively.</p> </li> <li> <p>Determine when to use LLMs, traditional software solutions, human intervention, or coordinated multi-agent approaches to achieve the best outcomes.</p> </li> <li> <p>Collaborate with operational and product teams to understand existing processes, identify high-value automation opportunities, and transform them into reliable production systems.</p> </li> <li> <p>Establish scalable architectural patterns and engineering standards for agentic systems as the organization grows.</p> </li> <li> <p>Take ownership of technical decisions and contribute to the overall direction of the AI engineering function.</p> </li> <h3><strong>Requirements</strong></h3> <p>The ideal candidate is a strong software engineer with hands-on experience building production-ready AI systems and the autonomy to solve complex technical challenges in a rapidly evolving environment. The following qualifications and skills are expected:</p> <ul data-spread="false"> <li> <p>Strong software engineering background, with proven experience independently delivering complex systems from initial concept through production deployment.</p> </li> <li> <p>Practical experience building and deploying AI or agentic systems that have operated in production environments.</p> </li> <li> <p>Demonstrated understanding of real-world AI engineering challenges, including reliability, latency, context management, failure modes, evaluation, and observability.</p> </li> <li> <p>Strong knowledge of agent architectures, tool use, structured outputs, context management, orchestration, evaluation frameworks, and feedback loops.</p> </li> <li> <p>Advanced practical experience with modern LLMs and the ability to build reliable workflows around probabilistic AI systems.</p> </li> <li> <p>Hands-on experience using coding agents and agentic development workflows as part of everyday software engineering.</p> </li> <li> <p>Ability to break down complex engin