Applied AI Engineer –

Applied AI Engineer (Remote) (Europe or UK - Required)

100k 150k Euro

Responsibilities

• Design and build the core primitives behind our agentic systems including memory context management tool-calling orchestration and feedback loops
• Move us from one-off AI solutions toward reusable infrastructure where new workflows can be introduced quickly and with predictable reliability
• Build the evaluation framework that allows us to understand how our agents perform and why they succeed or fail
• Make testing tracing debugging and evaluating AI systems as fundamental to our engineering process as unit testing traditional software
• Develop the systems that allow us to confidently assess an agentic workflow before deploying it into production
• Push forward how we use LLMs to build software itself
• Create workflows where coding agents and specialized subagents can explore repositories implement changes review architecture check conventions run evaluations and iterate with minimal human coordination
• Use agentic engineering workflows extensively in your own day-to-day development
• Design systems where specialized agents tools deterministic software and humans work together effectively
• Understand when a problem should be solved with an LLM when traditional software is the better solution and when multiple coordinated agents can materially improve the outcome
• Act as the bridge between complex operational workflows and engineering
• Work closely with our operational and product teams to understand how work actually happens across acquired agencies identify the highest-leverage opportunities for automation and turn them into reliable production systems
• Help define the architectural patterns we use for agentic systems as the company scales
• You wont be joining as engineer #20 on an established AI platform. You will be an early core member of the team with significant influence over our technical approach tooling and engineering standards

Requirements

• Strong software engineering background with experience independently delivering complex systems from idea through to production
• Hands-on experience building **AI or agentic systems that have operated in production**
• Experience dealing with real-world AI challenges such as reliability latency context management failure modes evaluation and observability
• Strong understanding of **agents tool use structured outputs context management orchestration evaluation and feedback loops**
• Advanced practical use of modern LLMs not simply using ChatGPT or Claude occasionally but understanding how to build reliable workflows around probabilistic systems
• Experience using **coding agents and agentic development workflows** as part of your own engineering process
• Experience decomposing complex engineering tasks across agents or specialized subagents and designing mechanisms for them to verify and improve their outputs
• Strong architectural judgment and ability to decide when to use LLMs deterministic software human intervention or a combination of approaches
• Experience with **TypeScript / ** or strong experience building AI systems in Python with the ability and willingness to apply that knowledge in a TypeScript-first environment
• High autonomy ownership and comfort making decisions under ambiguity
• Strong product judgment and ability to connect technical decisions to operational and business outcomes
• Strong communication skills and fluency in English
• Startup mentality: resilience adaptability and ability to thrive in a fast-paced environment