Staff AI Engineer
Job Description
<p><strong>About the Position</strong></p> <p>As a Staff AI Engineer, you’ll serve as a technical leader for our LLM-powered products at the forefront of marketing and advertising technologies. You’ll own critical architectural decisions, set quality bars, and lead multi‑team initiatives that drive measurable outcomes.</p> <p>As our Staff AI Engineer, you will lead the vision and execution of our data platform and LLM-powered products. You’ll own critical architectural decisions across data pipelines, model integration, model deployment and evals: turning high-level product and business requirements into robust, scalable data products that drive measurable outcomes for our Fortune 500 customers. This role spans data backend and ML engineering: from the reliability and cost efficiency of our pipelines to the outcome and performance of LLM-enabled features. You’ll raise the bar for data literacy across the department, craft and collaboration.</p> <p>You’ll be accountable for the health, cost, and evolution of key data product and data platforms, partnering closely with full-stack engineers, product, design, and devops to deliver outcomes our customers can trust.</p> <p>This role presents an exciting opportunity to shape the future of AI-driven technologies and make meaningful contributions to real-world applications.</p> <p>The role is linked with our location in London, but we are flexible about hybrid or remote work in The United Kingdom.</p> <p><strong>What You’ll Be Doing</strong></p> <ul> <li>Lead end-to-end architecture for data platforms and pipelines: scraping, data extraction, transformation, storage, serving, and ML/LLM integration, balancing performance, reliability, security, and cost.</li> <li>Incrementally scale pipelines and systems: design safe rollout plans and north star data-quality metrics to handle customer and traffic growth without impacting production.</li> <li>Translate business goals into actionable data products: assess high-level requirements, carve clear problem spaces, draft crisp RFCs, and sequence work into deliverable projects for the team.</li> <li>Establish and enforce engineering standards: testing strategy, evals, observability, data contracts, and security practices across services. Think through short-term and long-term goals to come up with fast go-to-market products, while planning ahead for productization.</li> <li>Up‑level the org: lead architecture reviews, codify patterns, mentor Senior Engineers, and multiply impact through documentation, code reviews, and pairing.</li> <li>Startup‑ready: flexible, comfortable with ambiguity and constant change; proactive about process, documentation, and reliability without over‑engineering.</li> <li>Lead the collaboration and define how AI engineers work cross-functionally with software engineers, devops, product managers and designers, to conceptualize and shape innovative and impactful solutions. Provide mentorship to junior team members and cultivate a culture of collaboration and innovation.</li> <li>Ship meaningful experiments: prototype data/ML capabilities, evaluate feasibility and ROI, and make pragmatic calls on productionalizing with an eye on operating costs and risk.</li> </ul> <p><strong>Qualifications</strong></p> <ul> <li>8+ years building and operating production data systems, including leading cross-cutting architectural changes, and deploying LLMs in real‑world scenarios at scale.</li> <li>Deep experience with Python and modern service architectures; strong system design and data modeling fundamentals.</li> <li>Extensive experience with training and deploying machine learning models, particularly within the NLP/LLM domain. Familiarity with infrastructure as co