ABOUT THE COMPANY

At Ocean, we’re on a mission to become the UK’s leading credit platform for people not served by the mainstream, helping them improve their financial wellbeing over their lifetime. This has been our mission for over 30 years, and it’s still the thing that drives us to do better and more for our customers.
We do this by helping our customers make informed decisions and access personal finance products.
If our mission sounds interesting, please keep reading!

ABOUT THE JOB

We’re looking for a creative and pragmatic AI Agent Engineer to help build the next generation of domain-specific AI agents — what we call “digital colleagues.” These agents will eliminate repetitive tasks, improve operational efficiency, and ensure regulatory compliance.
You’ll be at the forefront of applied AI, turning high-friction workflows into intelligent, secure, and scalable agent-led experiences. You will be single-minded and join with a strong purpose of driving measurable efficiencies in the way each department is operating enabling the business to grow faster whilst help foster a culture of AI first business ops.
If you enjoy pushing the limits of LLM capabilities in a fast-paced, mission-driven environment — you’ll feel right at home here.

SKILLS-WISE, YOU’LL DEFINITELY:

• 5+ years of expert-level Python development experience
• Strong experience with cloud-based AI deployment (AWS)
• Deep understanding of DevOps/MLOps and scalable infrastructure for AI systems
• Hands-on experience with LLMs, agent orchestration, vector stores and RAG workflows
• Excellent cross-functional collaboration and communication skills
• Proven ability to lead and mentor engineers or cross-functional teams
• Strong problem-solving skills and confidence making decisions amid ambiguity

WHAT YOU’LL BE DOING FOR US

A day in the life of this role could look like…

• Shadowing a product owner to map manual processes, then turning those into user stories, threat models, and agent blueprints
• Designing, building, and deploying agents using orchestration frameworks, vector stores, RAG pipelines, memory systems, and real-time APIs
• Iterating on prompts, reward strategies, and safety layers through A/B testing against human benchmarks
• Maintaining a library of reusable agent templates and creating documentation and enablement materials for the wider engineering and product teams

KEY RESPONSIBILITIES

• Map the AI agent ecosystem: Stay current with developments in LLMs, agent orchestration frameworks, vector databases, RAG patterns, and API-based toolchains.
• Uncover opportunities: Work with stakeholders to identify high-value use cases for agent-based automation that align with business goals
• Design agent workflows: Architect secure, auditable agent pipelines including prompt engineering, tool invocation, memory, fallback handling, and safety protocols
• Coordinate development: Partner with software and ML engineers to deliver robust agent implementations and validate performance
• Drive integrations: Connect agents to internal systems (CRMs, APIs, data lakes, knowledge bases) for full end-to-end automation
• Enable adoption: Deliver training, onboarding, and documentation to increase agent usage and success across teams
• Measure & improve: Monitor agent output, track usage metrics, and refine behaviour based on feedback and results
• Ensure compliance: Implement safeguards against hallucinations, and ensure compliance against our regulatory framework