Staff AI Engineer in London

Staff AI Engineer in London

London Full-Time 80000 - 100000 ÂŁ / year (est.) Home office (partial)
Bluefish

At a Glance

  • Tasks: Lead the architecture for AI-driven data platforms and pipelines, shaping innovative solutions.
  • Company: Join a cutting-edge tech firm at the forefront of marketing and advertising technologies.
  • Benefits: Flexible hybrid or remote work options, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic environment with mentorship opportunities and a culture of innovation.
  • Why this job: Make a real impact in AI technologies while collaborating with talented teams.
  • Qualifications: 8+ years in data systems, strong Python skills, and experience with LLMs.

The predicted salary is between 80000 - 100000 ÂŁ per year.

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. You will lead the vision and execution of our data platform and LLM‑powered products, 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 products 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.

Staff AI Engineer in London employer: Bluefish

As a Staff AI Engineer at our London-based company, you will join a dynamic and innovative team dedicated to shaping the future of AI-driven technologies. We pride ourselves on fostering a collaborative work culture that encourages continuous learning and professional growth, offering flexible hybrid or remote work options to support work-life balance. With a focus on impactful projects for Fortune 500 clients, you'll have the opportunity to lead architectural decisions and mentor fellow engineers, all while contributing to meaningful advancements in marketing and advertising technologies.
Bluefish

Contact Detail:

Bluefish Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff AI Engineer in London

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and data engineering. This is your chance to demonstrate your expertise and make a lasting impression on hiring managers.

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.

We think you need these skills to ace Staff AI Engineer in London

Architectural Design
Data Pipeline Development
Machine Learning Model Deployment
Python Programming
NLP/LLM Expertise
Infrastructure as Code
CI/CD Practices
Cloud Infrastructure Management
Operational Maturity
Data Preprocessing
Feature Engineering
Model Evaluation Techniques
Analytical Skills
Problem-Solving Skills
Communication Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Staff AI Engineer role. Highlight your experience in building data systems and deploying LLMs, as this will show us you’re a great fit for the position.

Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re passionate about AI and how your background makes you the perfect candidate. Share specific examples of your past work that demonstrate your leadership and technical skills.

Showcase Your Projects: If you’ve worked on relevant projects, don’t hesitate to include them! We love seeing real-world applications of your skills, especially those that involve data pipelines and ML integration. It gives us a better idea of what you can bring to the table.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!

How to prepare for a job interview at Bluefish

✨Know Your Tech Inside Out

As a Staff AI Engineer, you'll need to demonstrate your deep understanding of Python and modern service architectures. Brush up on your system design and data modelling fundamentals, and be ready to discuss your experience with deploying LLMs at scale. Prepare to explain complex concepts in simple terms, as you might have to communicate with non-technical stakeholders.

✨Showcase Your Leadership Skills

This role requires strong leadership abilities, so think about examples where you've guided teams or led architectural changes. Be prepared to share how you've mentored junior engineers and fostered collaboration across functions. Highlight any experiences where you've elevated the organisation through documentation, code reviews, or architecture reviews.

✨Prepare for Problem-Solving Scenarios

Expect to tackle real-world problems during your interview. Think of scenarios where you've had to navigate ambiguity or make pragmatic production calls. Be ready to discuss how you balance performance, reliability, and cost efficiency when designing data products, and how you approach scaling pipelines and systems.

✨Understand the Business Impact

It's crucial to translate business goals into actionable data products. Prepare to discuss how you've assessed high-level requirements and turned them into deliverable projects. Familiarise yourself with the metrics that matter, like data quality and ROI, and be ready to explain how your work has driven measurable outcomes for previous employers.

Staff AI Engineer in London
Bluefish
Location: London

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