About the Position
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.
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 evaluations: 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, balancing reliability, cost efficiency, and performance of LLM‑enabled features. You’ll raise the bar for data literacy across the department and craft collaborative solutions.
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. This role presents an exciting opportunity to shape the future of AI‑driven technologies and make meaningful contributions to real‑world applications. The role is linked with our location in London, but we are flexible about hybrid or remote work in the United Kingdom.
What You’ll Be Doing
- Lead end‑to‑end architecture for data platforms and pipelines: scraping, extraction, transformation, storage, serving, and ML/LLM integration, balancing performance, reliability, security, and cost.
- Incrementally scale pipelines and systems: design safe rollout plans and north‑star data‑quality metrics to handle customer and traffic growth without impacting production.
- 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.
- Establish and enforce engineering standards: testing strategy, evaluations, observability, data contracts, and security practices across services, aiming to launch fast go‑to‑market products while planning ahead for productization.
- Elevate the organization: lead architecture reviews, codify patterns, mentor senior engineers, and multiply impact through documentation, code reviews, and pairing.
- Navigate ambiguity and constant change: flexible, proactive about process, documentation, and reliability without over‑engineering.
- Collaborate across functions: work with software engineers, DevOps, product managers, and designers to shape innovative and impactful solutions, provide mentorship to junior team members, and cultivate a culture of collaboration and innovation.
- Ship meaningful experiments: prototype data/ML capabilities, evaluate feasibility and ROI, and make pragmatic production calls with an eye on operating costs and risk.
Qualifications
- 8+ years building and operating production data systems, leading cross‑cutting architectural changes, and deploying LLMs at scale.
- Deep experience in Python and modern service architectures; strong system design and data modeling fundamentals.
- Extensive experience with training and deploying machine learning models, especially within the NLP/LLM domain; proficiency in Python. Familiarity with infrastructure as code, CI/CD, and cloud infrastructure.
- Fluency in operational maturity: SLOs, on‑call/incident practices, and observability.
- Strong analytical and problem‑solving abilities, bias toward action and outcomes; experience with data preprocessing, feature engineering, and model evaluation techniques.
- Excellent communication skills, ability to explain complex technical concepts to non‑technical stakeholders. Demonstrated leadership experience, guiding and inspiring a team.
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