At a Glance
- Tasks: Lead the architecture of AI-driven data platforms and pipelines for innovative marketing solutions.
- Company: Join Bluefish, a dynamic startup at the forefront of AI marketing technology.
- Benefits: Competitive salary, equity package, remote work flexibility, and co-working day passes.
- Why this job: Shape the future of AI technologies and make a real impact in the marketing industry.
- Qualifications: 8+ years in full-stack systems, strong Python skills, and leadership experience.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 54000 - 84000 £ 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.
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.
You'll be accountable for the health, cost, and evolution of key data product and data platforms, partnering closely with AI 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, data 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, 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.
- Up-level the org: lead architecture reviews, codify patterns, mentor Senior Engineers, and multiply impact through documentation, code reviews, and pairing.
- Startup-ready: flexible, comfortable with ambiguity and constant change; proactive about process, documentation, and reliability without over-engineering.
- 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.
- 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.
Qualifications
- 8+ years building and operating production full-stack systems, including leading large-scale architectural changes or platform initiatives.
- Deep experience Python and modern service architectures; strong system design and data modeling fundamentals.
- 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 with a bias towards action and outcomes.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Demonstrated leadership experience, with the ability to guide and inspire a team.
What We Offer
- A dynamic role at the forefront of AI marketing technology with ample opportunities for personal and professional growth.
- Unique opportunity to join on the ground floor of a fast-moving startup building at the center of AI.
- Tackle challenging problems while disrupting the $300BN legacy martech industry.
- Join an experienced team where you will have immediate ownership and impact.
- Competitive salary and bonus appropriate for experience and company stage.
- Significant equity package appropriate for company stage.
- Wework co-working day-passes.
- PTO and remote work flexibility.
About Bluefish
Bluefish believes that AI represents the next major chapter of the internet – and that consumers will increasingly use AI to consume information and media online. On this new AI internet, brands will need new tools and technologies to tell their stories to consumers – and a new marketing ecosystem will be created around AI. Bluefish is building the platform that helps brands engage consumers on this new AI channel, with powerful enterprise tools to manage how their brand is represented in AI.
The Bluefish team is a tight-knit group of martech industry veterans who previously helped build foundational ad-tech platforms now owned by Meta and Microsoft. The company is backed by leading AI and data focused investors, including Crane Ventures, Swift Ventures, BloombergBeta, Firebolt Ventures, and Laconia Capital. We are a globally distributed team, with business operations based in New York City and engineering based in Europe.
Staff AI Engineer in London employer: Crane Venture Partners
Contact Detail:
Crane Venture Partners 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 or GitHub repository showcasing your projects, especially those related to AI and data platforms. This gives hiring managers a tangible sense of what you can bring to the table.
✨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 Bluefish.
We think you need these skills to ace Staff AI Engineer in London
Some tips for your application 🫡
Show Your Technical Leadership: As a Staff AI Engineer, we want to see your experience in leading architectural decisions and multi-team initiatives. Make sure to highlight any past projects where you’ve taken charge and driven measurable outcomes.
Be Clear and Concise: When translating business goals into actionable data products, clarity is key. Use crisp language to describe your problem-solving approach and how you’ve turned high-level requirements into successful projects.
Demonstrate Collaboration Skills: We value teamwork! Share examples of how you’ve worked cross-functionally with engineers, product managers, and designers. Highlight your mentorship experiences and how you’ve fostered a culture of collaboration.
Tailor Your Application: Make your application stand out by tailoring it to our specific needs. Mention your familiarity with Python, CI/CD, and cloud infrastructure, and don’t forget to apply through our website for the best chance!
How to prepare for a job interview at Crane Venture Partners
✨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 how you've led large-scale architectural changes in the past.
✨Showcase Your Leadership Skills
This role requires strong leadership experience, so prepare examples of how you've guided and inspired teams. Think about times when you've mentored junior engineers or led cross-functional collaborations, and be ready to share these stories during the interview.
✨Translate Business Goals into Technical Solutions
Be prepared to discuss how you can turn high-level business requirements into actionable data products. Think through specific examples where you've assessed requirements and delivered projects that drove measurable outcomes, especially in a fast-paced environment.
✨Communicate Clearly with Non-Technical Stakeholders
Excellent communication skills are crucial for this position. Practice explaining complex technical concepts in simple terms, as you'll need to convey ideas to non-technical stakeholders. Consider preparing a few scenarios where you've successfully bridged the gap between tech and business.