At a Glance
- Tasks: Design and deliver cutting-edge AI solutions in a hands-on engineering role.
- Company: Join UST, a tech leader transforming lives through responsible AI.
- Benefits: Competitive pay, flexible work arrangements, and opportunities for professional growth.
- Other info: Collaborative environment with excellent career advancement opportunities.
- Why this job: Make a real-world impact by building scalable AI systems that solve complex problems.
- Qualifications: Strong Python skills and experience with Generative AI applications required.
The predicted salary is between 63000 - 77000 £ per year.
Generative AI Scientist – Agent‑Based Systems London (4 days onsite) Contract (Inside IR35) or Fixed‑Term Employment
The Opportunity at UST
At UST, we transform lives through the power of technology, combining deep engineering expertise, responsible AI, and an empathy‑first mindset to deliver meaningful, real‑world impact. We are seeking a Generative AI Scientist to design and deliver agent‑based, AI‑enabled solutions integrated into complex enterprise environments. This is a hands‑on engineering role, focused on building production‑grade AI systems that move beyond experimentation into scalable, secure, and measurable outcomes for our clients. You’ll work closely with UST’s engineering teams, AI specialists, and business stakeholders to translate high‑value use cases into robust solutions.
What You’ll Be Doing
- Build Agent‑Based AI Systems
- Design and develop multi‑agent orchestration workflows (supervisor / sub‑agent patterns)
- Implement multi‑step, asynchronous pipelines to solve complex enterprise problems
- Integrate AI workflows into client systems via secure, well‑designed APIs
- Develop LLM‑Enabled Applications
- Deliver end‑to‑end LLM‑powered features in production environments
- Design effective prompting strategies and context management
- Implement structured outputs, validation, and safety guardrails, aligned to responsible AI principles
- Design Retrieval & Data Pipelines (RAG)
- Build and optimise retrieval‑augmented generation (RAG) pipelines
- Work with vector search and similarity retrieval
- Search and indexing systems
- Embeddings and content storage
- Caching strategies for performance and scalability
- Backend & Platform Engineering
- Develop Python‑based backend services (APIs, integrations, orchestration layers)
- Apply strong engineering discipline across testing, observability, and error handling
- Contribute to reusable assets and patterns within UST’s AI ecosystem
- Cloud‑Native Delivery (AWS)
- Deploy and operate scalable solutions on AWS
- Ensure best practices across security and IAM, reliability and performance, CI/CD and environment management
What We’re Looking For
- Strong experience in Python backend engineering
- Hands‑on delivery of Generative AI / LLM‑based applications
- Experience with agent frameworks (e.g. LangChain, LlamaIndex, or similar)
- Retrieval‑based systems (RAG, vector databases, embeddings)
- APIs, microservices, and asynchronous workflows
- Experience deploying production systems in AWS environments
Nice To Have
- Experience with multi‑agent architectures
- Exposure to productionising AI systems at scale
- Knowledge of data pipelines, search infrastructure, and platform engineering
Skills: Generative AI, AI Governance, Solutioning, Compliance Management, Prompt Engineering, Stakeholder Management
Generative AI Scientist – Agent‑Based Systems_London_Contract (Specialist I - ML Engineering) employer: UST
As a Principal Data Engineer at our company, you will thrive in a dynamic and innovative work culture that prioritises technical excellence and continuous learning. With opportunities for mentorship and collaboration across diverse teams, you will play a pivotal role in shaping the future of our cloud-scale data platform while enjoying the flexibility of a hybrid work environment in Nottingham or London. We are committed to fostering your professional growth and providing a supportive atmosphere where your contributions directly impact our success.
StudySmarter Expert Advice🤫
We think this is how you could land Generative AI Scientist – Agent‑Based Systems_London_Contract (Specialist I - ML Engineering)
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like UST before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like UST.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like UST.
We think you need these skills to ace Generative AI Scientist – Agent‑Based Systems_London_Contract (Specialist I - ML Engineering)
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at UST, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to UST, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab UST’s attention and show the tangible impact of your work.
How to prepare for a job interview at UST
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at UST.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at UST.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at UST.
