At a Glance
- Tasks: Build and deploy AI systems to enhance investment workflows and research processes.
- Company: Specialist investment firm with a focus on innovative AI solutions.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on high-value use cases.
- Why this job: Make a real impact in finance by developing cutting-edge AI tools.
- Qualifications: Experience in building LLM applications and familiarity with cloud platforms.
The predicted salary is between 60000 - 80000 £ per year.
A specialist investment firm is looking for a hands-on AI Engineer to build and deploy production-grade AI systems that directly support their research and investment workflows.
About the role
You will work closely with portfolio managers and analysts to design, build and deploy reliable AI-driven tools that raise the quality, speed and consistency of their investment processes. Ownership from early prototype through to production deployment, monitoring and ongoing iteration.
What you'll do
- Equity research tooling
- Analyse, summarise and extract structured data from filings, transcripts, external research and internal notes
- Automate screening, idea generation and other repetitive research tasks
- Build internal APIs and lightweight UIs that make these tools genuinely usable for the investment team
- System ownership
- Take full-stack system ownership from prototype to production
- Integrate LLMs and other models with proprietary research data, third-party market data feeds and existing analyst workflows
- Design and implement RAG systems across internal research, filings and datasets
- Governance & collaboration
- Implement practical model risk controls and maintain robust, auditable systems
- Partner with investment professionals to surface and prioritise high-value use cases
What we're looking for
- Proven track record building, deploying and maintaining end-to-end LLM applications including prompt engineering, API integration and agentic orchestration frameworks
- Hands-on experience with at least one major cloud platform (AWS, GCP or Azure)
- AI & LLM expertise
- Experience with LLM APIs such as OpenAI or Anthropic
- Solid understanding of retrieval-augmented generation (RAG), embeddings and vector databases
- Knowledge of hallucinations risk and migration strategies
- Experience with SQL and ability to build and maintain data pipelines
- Nice to have
- Prior experience applying AI in financial services, investment research or another regulated environment
- Experience with financial data sources – filings, market data, earnings calls, sell-side research and transcripts
AI Engineer employer: TechByte Talent Ltd
As a leading specialist investment firm located in the heart of London, we pride ourselves on fostering a dynamic and innovative work culture that empowers our employees to take ownership of their projects. Our AI Engineers benefit from a collaborative environment where they can directly impact investment workflows while enjoying opportunities for professional growth and development. With a focus on cutting-edge technology and a commitment to excellence, we offer a rewarding career path for those looking to make a meaningful contribution in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Reach out to professionals in the investment and AI sectors on LinkedIn. Join relevant groups and participate in discussions to get your name out there. You never know who might have a lead on that perfect AI Engineer role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to finance or investment research. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and understanding of the financial sector. Be ready to discuss how you've built and deployed AI systems in the past, and how they can be applied to improve investment processes.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find and apply for roles that match your skills. Plus, it shows you're genuinely interested in joining our team and contributing to our mission.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Engineer role. Highlight your experience with LLM applications, cloud platforms, and any relevant projects that showcase your skills in building and deploying AI systems.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our needs. Don’t forget to mention any experience you have in financial services or investment research.
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, demonstrating your hands-on experience can really set you apart.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at TechByte Talent Ltd
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLM applications and the specific technologies mentioned in the job description. Be ready to discuss your hands-on experience with cloud platforms like AWS, GCP, or Azure, and how you've integrated AI into real-world applications.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex problems in previous roles, especially those related to equity research tooling or automating repetitive tasks. Highlight your ability to design and implement systems that improve investment processes.
✨Understand the Financial Context
Familiarise yourself with financial data sources and the investment research landscape. Being able to speak the language of portfolio managers and analysts will show that you can effectively collaborate and prioritise high-value use cases.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to AI and how they envision the role of an AI Engineer within their investment workflows. This not only shows your interest but also helps you gauge if the company is the right fit for you.
