At a Glance
- Tasks: Design and build cutting-edge AI systems that solve real business problems.
- Company: Leading global investment firm with a strong commitment to AI innovation.
- Benefits: Autonomy, visibility, and the chance to influence AI strategy from day one.
- Other info: Dynamic role with significant ownership and exposure to complex datasets.
- Why this job: Shape AI capability in a greenfield environment with immediate impact.
- Qualifications: Experience in production AI systems and strong Python engineering skills.
The predicted salary is between 80000 - 100000 £ per year.
A leading global investment business is looking to make its first dedicated AI Engineering hire — a rare opportunity to build and shape AI capability from day one inside a highly respected organisation managing tens of billions in assets. This is far beyond experimentation or internal demos. The successful candidate will design, build, and own production-grade AI systems that solve real business problems — from advanced RAG pipelines and agentic workflows to internal AI platforms used across the organisation.
This role offers genuine autonomy, visibility, and the chance to influence AI strategy, architecture, and engineering standards at an early stage.
Why this opportunity stands out- Foundational AI hire with significant ownership and influence
- Greenfield environment with freedom to shape tooling, architecture, and best practices
- Direct exposure to complex, high-value datasets and workflows
- Strong long-term investment and commitment to AI from leadership
- Opportunity to build systems with immediate, measurable impact
- Build production-grade RAG pipelines across complex unstructured data
- Design and deploy multi-agent AI systems and orchestration frameworks
- Integrate LLMs across OpenAI, Anthropic, and open-source ecosystems
- Develop semantic search, vector database, and graph-based retrieval systems
- Own AI evaluations, observability, governance, and reliability
- Build internal AI products that enhance decision-making and operational efficiency
- Proven experience shipping production AI/LLM systems used by real users
- Strong end-to-end engineering capability — from architecture through deployment
- Deep Python and backend engineering experience
- Strong understanding of modern AI tooling, RAG, and agentic systems
- Comfortable operating in ambiguity and building from scratch
- Uses AI tooling aggressively, but critically and responsibly
- Cares about product quality, reliability, and business outcomes — not just models
- Python
- FastAPI
- LangGraph/LangChain
- Vector Databases
- Graph Databases
- OpenAI/Anthropic
- Azure AI
- RAG
- Agentic Systems
- APIs
- CI/CD
- Cloud Infrastructure
This is an exceptional opportunity for an ambitious AI Engineer looking to build something meaningful at the frontier of applied AI — with the autonomy, backing, and technical scope to make a genuine impact.
Generative AI Engineer in Slough employer: Harrington Starr
Join a leading global investment business as a Founding AI Engineer, where you will have the unique opportunity to build and shape AI capabilities from the ground up. With a strong commitment to AI from leadership, this role offers genuine autonomy, direct exposure to complex datasets, and the chance to influence AI strategy in a greenfield environment. Enjoy a collaborative work culture that prioritises innovation and employee growth, making it an excellent place for ambitious engineers to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Generative AI Engineer in Slough
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, attend meetups, and connect on LinkedIn. The more you engage with the community, the better your chances of landing that dream role.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those involving production-grade AI systems. This will give potential employers a taste of what you can do and how you think.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with RAG pipelines and multi-agent systems — they want to see your expertise in action!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who are eager to shape the future of AI. Your next big opportunity could be just a click away!
We think you need these skills to ace Generative AI Engineer in Slough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Generative AI Engineer. Highlight your experience with production-grade AI systems and any relevant projects that showcase your skills in Python, FastAPI, and RAG pipelines.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about building AI capabilities from the ground up. Share specific examples of how you've influenced AI strategy or architecture in previous roles to show us what you can bring to the table.
Showcase Your Technical Skills:Don’t just list your skills; demonstrate them! If you’ve worked with LLMs, vector databases, or agentic systems, include details on how you used these technologies to solve real business problems. We want to see your hands-on experience!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Harrington Starr
✨Know Your AI Stuff
Make sure you brush up on your knowledge of generative AI, RAG pipelines, and agentic systems. Be ready to discuss your past experiences with production-grade AI systems and how you've tackled real business problems using these technologies.
✨Showcase Your Engineering Skills
Prepare to demonstrate your end-to-end engineering capabilities. Bring examples of your work in Python, FastAPI, and any relevant frameworks. Highlight how you've designed and deployed systems that have made a measurable impact.
✨Embrace the Greenfield Challenge
This role is all about building from scratch, so be ready to talk about how you approach ambiguity and create solutions in uncharted territory. Share your thoughts on best practices for tooling and architecture in a greenfield environment.
✨Focus on Business Outcomes
Remember, it’s not just about the tech; it’s about how it drives results. Be prepared to discuss how your AI solutions have enhanced decision-making and operational efficiency in previous roles. Show that you care about product quality and reliability.
