Nathan Wills

Applied AI Engineer  I am working with a fast growing AI company building an enterprise grade AI workspace used by major financial institutions to produce and validate client ready work. The platform replaces complex manual workflows with automated AI systems that scale across global teams and has grown rapidly with backing from top tier investors. This role is for engineers who want to build and ship production systems. You will own core parts of the AI agent infrastructure, including multi agent systems, RAG pipelines, and evaluation frameworks. The work is hands on and production focused, covering backend services, AI infrastructure, and delivery at scale. What you will doBuild and deploy backend services and APIs, Python preferred using Django or FastAPIProductionise AI features including RAG, agent orchestration, and evalsCreate data pipelines for training, evaluation, and continuous improvementEnsure performance, reliability, and security across the stackWork closely with founders, engineers, and product teamsWhat we are looking forFive plus years of software engineering experienceProven experience deploying AI applications into productionStrong backend engineering skills and database fundamentalsExperience with cloud infrastructure, Docker, Kubernetes, and CI CDBackground workers, task queues, and Redis experienceFamiliarity with LLM evaluation, monitoring, and safetyDegree from a Russell Group university or equivalent top tier academic background, or alternatively extensive engineering expertise with clear, relevant production experienceThis is a demanding, in office environment with high ownership, shifting priorities, and strong technical standards. You will work directly with founders who have built and exited venture backed companies. If you are an Applied or Agentic AI Engineer looking for real ownership and the chance to build core systems from the ground up, this is worth a conversation.

We are looking for a GenAI Engineer to join a growing Consulting organisation focused on AI solutions for the varied industries. You will play a key role in developing and integrating enterprise-level AI systems, contributing to the next generation of intelligent tools used by their clients. What You’ll DoDesign, build, and deploy GenAI applications using OpenAI APIs and LLM frameworksDevelop and optimise RAG pipelines for production useCollaborate with cross-functional teams to integrate AI into existing SaaS productsWrite clean, efficient, and scalable code, primarily in PythonContribute to architecture and design discussions around AI deployment and automationEngage with clients and internal teams to ensure alignment on project goalsWhat We’re Looking ForProven background in software development within SaaS or enterprise environmentsStrong practical experience using OpenAI APIs in commercial or large-scale settingsSolid understanding of LLMs, prompt engineering, and model deploymentHands-on experience with RAG pipelines and data retrieval optimisationExcellent communication and stakeholder management skillsAble to work independently and within collaborative teamsNice to HaveFrench for collaboration with teams in LausanneGerman for client interactions in ZurichWhy JoinFully remote flexibility with the option to work near Zurich or LausanneStable, long-term AI projects within the financial sectorClear growth trajectory with opportunities to contribute to upcoming initiativesSupportive, collaborative environment with positive team sentiment

I am working on a Lead AI Developer role for a UK based team delivering AI solutions into complex, non technical environments. This is a hands on role for someone who codes daily but also leads from the front. You would sit between senior stakeholders and delivery teams, shaping requirements, explaining trade offs, and guiding technical direction without relying on formal authority. What the role actually needs. You are still a builder. Strong in C#, .NET, and Python, comfortable shipping production systems, deploying to cloud, and working with modern AI patterns like LLMs, RAG, and agent based workflows. At the same time, you are confident in front of clients. You can run a requirements session, challenge vague asks, surface constraints early, and translate technical decisions into language that non engineers trust. You have led delivery through influence. Mentoring developers, setting standards, steering architecture discussions, and handling competing priorities when stakeholders want different outcomes. What you would be doingWorking directly with clients to turn real world problems into clear technical designs and delivery plansLeading backlog refinement, sprint planning, and technical prioritisationBuilding and deploying AI enabled features across a Microsoft and Azure focused stackExplaining feasibility, risk, and trade offs in a way that helps stakeholders make decisionsRaising the bar for engineering quality through reviews, coaching, and exampleWhat tends to work well herePeople who have been the technical lead in client facing environmentsDevelopers who enjoy ambiguity and creating clarity rather than waiting for perfect specsEngineers who can say no when needed, and explain why in a constructive wayIf you are interested in this position, feel free to send your updated CV and we'll be in touch if this is a match.