Job Title
London (On-site, London Farringdon)
Full-time, salary: £60,000-80,000
Job Summary Travtus is looking for an AI Engineer to help design, build, and optimise the core AI platform capabilities that power agent-based products and workflows.
This role is focused on platform development. It is responsible for shaping how LLM-powered agents are designed, orchestrated, tested, monitored, and improved in production. The role sits at the intersection of prompt engineering, agent architecture, solution design, and platform capability development.
You will define how agents interact with tools, APIs, and downstream services, and help specify the requirements and contracts for the services they depend on. You will work closely with platform engineers , who build the APIs and services consumed by agents, and with product engineers , helping ensure agent capabilities support strong user experience and front-end design.
This role also includes working on patterns where prompt outputs are used as code to support interface generation, front-end behaviour, and rapid product iteration. You will also own the LLM and prompt tooling lifecycle, from prompt management through evaluation, testing, and continuous improvement.
This is a hands-on senior role for someone who combines deep technical skill with strong systems thinking and a practical approach to building scalable, usable, and production-ready AI capabilities.
About Travtus
Travtus is transforming the Housing Industry with our Everyday (AI)™ platform. We bring intelligence and automation together in one place so teams can move faster and work smarter. By delivering everyday AI decisions and workflows across the systems operators already use daily, our platform improves efficiency while enhancing the resident experience.
About the RoleKey Responsibilities
- Design and developmulti-agent promptsand orchestration patterns
- Define howagents, tools, APIs, services, and platform componentsinteract, including requirements, contracts, and integration patterns
- Work alongsideplatform engineersto define the APIs and services that agents consume and use
- Work closely withproduct engineersto support user experience and front-end design, including the use ofprompt outputs as code
- OwnLLM and prompt toolingacross the full lifecycle, from prompt management and versioning through evaluation, testing, and optimisation
- Design requirements for downstream and supporting services that enable agent execution, workflow control, observability, and integration
- Lead theresearch, evaluation, and selection of frameworksfor agent orchestration, tool use, evaluation, observability, and deployment
- Performmodel selectionbased on use case fit, quality, latency, scalability, and cost
- Design and implementtools and function-calling patternsfor agent-based systems
- Carry outprompt tuningand iterative optimisation of agent behaviour and output quality
- Monitor, debug, and continuously tuneagents in development and production
- Design forperformance, scalability, reliability, usability, maintainability, and cost efficiency
- Define and executetesting strategiesfor LLM agents and platform-level AI workflows
- Integration test agents end to endwith other parts of the platform to ensure reliability across workflows, services, and user-facing experiences
- Buildproofs of concept and prototypesto validate architectures, frameworks, and new platform capabilities
- Produce end-to-endsolution designsfor AI platform components and services
- UseAI to improve software development, including prototyping, implementation, testing, debugging, and engineering productivity
- Collaborate across engineering and product teams to translate business and technical goals into robust platform capabilities
Requirements
The successful applicant will be a natural problem-solver with an affinity for automation, efficiency, and AI-driven solutions with excellent communication and collaboration skills across both technical and non-technical teams.
Must have requirements:
- Strong experience designing, building, and deployingLLM-based applicationsoragentic systems
- Demonstrated expertise inprompt engineering, prompt tuning, and structured output design
- Experience designingmulti-agent workflowsand orchestration logic
- Strong understanding ofAPI design, service integration, and interface contracts
- Experience owning or working withprompt management, evaluation, and testing tooling
- Experience working with or defining requirements forplatform servicesthat support AI applications
- Experience evaluating and selectingmodels, frameworks, and AI tooling
- Practical experience withtool use, function calling, workflow control, and system integration
- Experience defining and implementingtesting and evaluation strategiesfor LLM systems
- Experience withend-to-end and integration testingacross complex platform workflows
- Strong understanding ofperformance optimisation, including latency, throughput, scalability, and cost trade-offs
- Experience monitoring and improving AI systems in production
- Strong software engineering skills and experience building production-grade systems
- Ability to work effectively with bothproduct engineersandplatform engineers
- Ability to produce clearsolution designsand communicate technical decisions effectively
- Comfortable working across experimentation, architecture, and delivery
Nice to have requirements: Experience with agent orchestration frameworks and evaluation platforms
- Familiarity with observability, tracing, and monitoring for AI systems
- Experience designing guardrails, controls, and failure handling for AI workflows
- Experience supporting front-end or UX-oriented engineering through AI-assisted design or generation patterns
- Experience with code generation or structured prompt outputs used in software delivery workflows
- Experience with cloud-native or distributed production environments
- Background in solution architecture, or applied AI systems
- Experience using AI to improve internal engineering productivity and delivery
What Success Looks Like
- The AI platform provides a strong, scalable foundation for agent-based products and workflows
- Agents, tools, APIs, and service integrations are reliable, testable, and production-ready
- LLM and prompt tooling supports disciplined prompt management, evaluation, testing, and continuous improvement
- Platform capabilities are designed with strong usability, maintainability, and operational robustness
- Agent outputs support high-quality product experiences, including front-end and UX use cases where appropriate
- Model, prompt, and framework choices are evidence-based and continuously optimised
- Agents are integration tested end to end with the wider platform and perform reliably across real workflows
- New ideas can be rapidly validated through POCs and evolved into durable platform capabilities
- Product engineers and platform engineers can work effectively around clear contracts, services, and orchestration patterns
- AI is used effectively both within the product and to improve software development practices
About the Team
We are a dedicated team, working in a truly collaborative style, where everyone is heard and brings something valuable to the conversation. Constantly pushing boundaries to create groundbreaking solutions for our customers. We are fundamentally challenging the way one of the largest industries in the world operates, and our commercial success pays testament to the skill, commitment and passion that our team displays every day.
Working together in person fuels our best ideas and innovations, which is why all team members spend at least three days a week in our London office.
Benefits
- Be part of a growing, mission-driven startup with global ambitions
- Exposure to cutting-edge AI technology in a practical, high-demand sector
- Collaborative, fast-paced team culture with space to innovate and grow
- Full-time, salary: £60,000-80,000
- On-site working model with a modern London office (Farringdon)
- Private Healthcare
- Pension
- Deliveroo Allowance
Help us shape the future of technology. Apply Now!
