Contract Role: Agentic AI Engineer – £1000–£1300 Per Day PAYE - Global Investment Bank
Location: London or Glasgow (On-site, 5 days/week)
Duration: 12 months (option to go perm after)
Industry: Global Tier-1 Investment Bank
Background: Open – Big Tech or AI-first companies welcome
Build autonomous AI systems that change how 60,000+ engineers operate worldwide.
This is where AI stops being theory—and becomes global infrastructure.
This Is Not Just a Role — It’s a Front-Row Seat to the Next Leap in AI:
We’re assembling a specialised handpicked lean Agentic AI team within one of the world’s most powerful financial institutions—an organisation already known for its scale, security, and relentless investment in emerging technologies. You’ll join a focused, fast-moving unit that sits at the heart of this bank’s AI transformation strategy.
Here, autonomous agents aren’t a concept—they’re the roadmap.
This team is building LLM-powered systems that think, reason, and act, helping 60,000+ engineers and technologists automate complex workflows, accelerate delivery, and eliminate friction. This isn’t chatbot work. This is AI with real-world agency—deployed into live production environments where milliseconds and precision matter.
What You’ll Be Doing (Day 1 to Day 100)
- Design & Build AI Agents: You’ll architect and implement autonomous systems powered by LLMs that execute multi-step tasks inside highly complex and regulated software environments.
- Bridge Research & Production: Experiment with techniques like Retrieval-Augmented Generation (RAG), embeddings, prompt chaining, and fine-tuning, and turn them into robust, production-grade tools.
- Own the ML Lifecycle: From experimentation to live deployment—write, test, scale, and monitor Python-based ML systems with tight performance and latency requirements.
- Scale Impact Across the Organisation: Your work will directly affect thousands of engineers by eliminating cognitive bottlenecks, streamlining access to knowledge, and enabling AI-assisted development workflows.
- Push What’s Possible with LLMs: You’ll go beyond the basics—embedding agent memory, reasoning over tools and environments, integrating external APIs, and helping models adapt over time.
Why This Role Is Career-Defining
True Autonomy in AI: This is one of the few places globally where you'll work on agentic AI with live deployment at this scale. Your ideas won’t die in a research doc—they’ll become production systems used every day, directly impacting the global economy.
Unparalleled Impact: This isn’t a niche project. Your work will directly affect 60,000+ developers and engineers, streamlining how they work, build, and deliver inside a massive, global institution.
Elite Team, Elite Tools: Join a curated squad of top-tier ML engineers, AI researchers, and systems architects with executive buy-in, enterprise resources, and a mandate to experiment, deliver, and scale.
No Legacy Constraints: While you’ll be inside a bank, you won’t be trapped in legacy tech. This team works with modern tooling, top-tier hardware, and the freedom to build right—from the ground up - a start up environment with all the financial backing.
The Opportunity to Go Permanent: This isn’t just a contract gig—it’s a launchpad. The organisation is open to making this a permanent position (optional) for those who thrive and want to continue at the bleeding edge.
Your Toolkit & Ecosystem:
- Languages: Python (essential), plus Java or C++ (helpful)
- LLMs: GPT, Claude, LLaMA, open-source models, fine-tuned variants
- Frameworks: PyTorch, TensorFlow, LangChain, Transformers, HuggingFace
- Infra: AWS (SageMaker, EKS), Kubernetes, Docker, GitOps CI/CD
- MLOps: Ray, MLFlow, distributed training, GPU scheduling, A/B testing
- Techniques: Prompt engineering, RAG, few-shot learning, embeddings, agent planning and reasoning, graph-based methods
What You Bring to the Table:
- MSc or PhD in Computer Science, Machine Learning, AI, or a closely related field.
- Hands-on experience with production-grade ML/AI, especially in NLP or Generative AI domains.
- Deep understanding of LLM architecture and behaviour, from prompt engineering to inference optimisation.
- You’ve built real-world systems using embeddings, fine-tuning, or inference-serving pipelines at scale.
- You’re highly autonomous—able to drive projects from scratch in ambiguous problem spaces.
- You’re performance-conscious—able to optimise for speed, cost, and accuracy in demanding environments.
- You care deeply about usability, transparency, and responsible deployment.
Bonus Experience That’ll Make You Stand Out:
- Experience building agent-based architectures or intelligent orchestration layers.
- Familiarity with agent memory/state management, recursive reasoning, or tool use in LLMs.
- Exposure to graph neural networks, recommender systems, or structured search/retrieval.
- Experience with multi-agent systems, workflow orchestration, or simulation environments.
- Experience in fast-paced product environments (e.g., Big Tech, AI-first start-ups, R&D labs).
Who This Role Is For:
This is ideal for someone who’s:
- Built or contributed to real-world LLM or agent-based systems.
- Hungry to move fast, solve hard problems, and see their work go live.
- Looking for purpose, scale, and technical depth—all in one role.
- Eager to work on the next frontier of enterprise AI—not just talk about it.
If you’re looking for more than just another ML job—if you want to create intelligent systems that act, learn, and scale—we want to speak with you.
Get in touch and apply today - let’s talk about how you can be part of something truly transformative.
