Forward Deployed AI Engineer

Overview We are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer‑facing role that combines deep infrastructure expertise with a passion for solving real‑world problems in drug discovery and protein engineering. Who We Are At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Our team has co‑developed DeepMind’s Nobel‑prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems and high‑throughput protein screening platforms. We work with some of the brightest minds in generative AI and biology, fostering a culture of trust across our London and San Francisco sites. Who You Are You have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field and a solid grounding in software engineering principles and modern ML frameworks. You have built systems that access large models via APIs, and have significant experience designing, deploying and maintaining infrastructure for large‑scale model serving. You have hands‑on experience building robust API layers around ML models. You are customer‑facing and delivery‑oriented. You have direct experience deploying AI systems for external customers, can translate complex technical concepts into clear language for non‑technical stakeholders, and thrive in environments where customer success is the primary measure of your work. You are fluent in cloud infrastructure. You have hands‑on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud‑native architectures. You are a strong communicator and collaborator. You work effectively across functions – with research scientists and business executives alike – and are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations. You are mission‑driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond, and thrive in a dynamic, fast‑paced environment where priorities can shift. What Sets You Apart You have experience with bio or protein design models and have worked on ML‑driven projects in computational biology, protein design, or related life‑science domains. You have contributed to generative modelling innovation through publications, open‑source work, or impactful product features. You have built production enterprise software that meets enterprise‑grade requirements for security, compliance, auditability and uptime. You have pharma or biotech industry experience and understand regulatory, data‑governance requirements and scientific workflows common in these organisations. Your Responsibilities Customer deployment & integration Drive the end‑to‑end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure. Design and build production‑grade API integrations, data pipelines and model‑serving infrastructure tailored to each customer’s requirements. Work on‑site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions. Ensure deployments meet enterprise standards for security, performance and reliability. Customer advocacy & product feedback Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time on‑site at international partner locations as needed. Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams. Collaborate with internal teams to shape the product roadmap based on real‑world deployment learnings. Create technical documentation, integration guides and best‑practice resources for customers. Self development Stay on top of the latest developments in ML infrastructure, model serving and cloud‑native tooling. Gain a strong working understanding of protein and cell biology as it relates to our product. Participate in knowledge sharing and organise or present at our internal reading group. Benefits Private health insurance Pension contributions Generous leave policies (including gender‑neutral parental leave) Hybrid working Travel opportunities and more We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills. #J-18808-Ljbffr