At a Glance
- Tasks: Design and optimise AI platforms for innovative agent-based products.
- Company: Join a mission-driven startup at the forefront of AI technology.
- Benefits: Competitive salary, private healthcare, pension, and Deliveroo allowance.
- Other info: Dynamic team culture with opportunities for innovation and growth.
- Why this job: Work with cutting-edge AI tech and make a real impact in a collaborative environment.
- Qualifications: Experience in LLM applications, prompt engineering, and API design.
The predicted salary is between 60000 - 80000 £ per year.
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. The role focuses on platform development and 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 to 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 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 with deep technical skill, strong systems thinking, and a practical approach to building scalable, usable, and production-ready AI capabilities.
Responsibilities
- Design and develop multi-agent prompts and orchestration patterns
- Define how agents, tools, APIs, services, and platform components interact, including requirements, contracts, and integration patterns
- Collaborate with platform engineers to define the APIs and services that agents consume
- Work with product engineers to support user experience and front-end design, including the use of prompt outputs as code
- Own LLM and prompt tooling across the full lifecycle, from prompt management and versioning through evaluation, testing, and optimisation
- Design requirements for downstream and supporting services enabling agent execution, workflow control, observability, and integration
- Lead the research, evaluation, and selection of frameworks for agent orchestration, tool use, evaluation, observability, and deployment
- Perform model selection based on use case fit, quality, latency, scalability, and cost
- Design and implement tools and function-calling patterns for agent-based systems
- Carry out prompt tuning and iterative optimisation of agent behaviour and output quality
- Monitor, debug, and continuously tune agents in development and production
- Design for performance, scalability, reliability, usability, maintainability, and cost efficiency
- Define and execute testing strategies for LLM agents and platform-level AI workflows
- Integration test agents end to end with other parts of the platform to ensure reliability across workflows, services, and user-facing experiences
- Build proofs of concept and prototypes to validate architectures, frameworks, and new platform capabilities
- Produce end-to-end solution designs for AI platform components and services
- Use AI to improve software development, including prototyping, implementation, testing, debugging, and engineering productivity
- Collaborate with 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.
- Strong experience designing, building, and deploying LLM-based applications or agentic systems
- Demonstrated expertise in prompt engineering, prompt tuning, and structured output design
- Experience designing multi-agent workflows and orchestration logic
- Strong understanding of API design, service integration, and interface contracts
- Experience owning or working with prompt management, evaluation, and testing tooling
- Experience working with or defining requirements for platform services that support AI applications
- Experience evaluating and selecting models, frameworks, and AI tooling
- Practical experience with tool use, function calling, workflow control, and system integration
- Experience defining and implementing testing and evaluation strategies for LLM systems
- Experience with end-to-end and integration testing across complex platform workflows
- Strong understanding of performance 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 both product engineers and platform engineers
- Ability to produce clear solution designs and communicate technical decisions effectively
- Comfortable working across experimentation, architecture, and delivery
Nice to Have
- 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. We push boundaries to create solutions for our customers. 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
AI Engineer employer: Travtus
Travtus is an exceptional employer that fosters a collaborative and innovative work culture, where every team member's voice is valued. Located in the vibrant Farringdon area of London, employees benefit from exposure to cutting-edge AI technology and a supportive environment that encourages professional growth and creativity. With competitive salaries, private healthcare, and a focus on work-life balance, Travtus offers a rewarding experience for those looking to make a meaningful impact in the AI sector.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI space. Attend meetups, conferences, or even online webinars. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to LLMs and agent-based systems. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions related to AI engineering and be ready to discuss your past experiences in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Travtus.
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-based applications, prompt engineering, and any relevant projects that showcase your skills. We want to see how your background aligns with what we're looking for!
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 skills can contribute to our team. Be sure to mention specific experiences that relate to the responsibilities outlined in the job description.
Showcase Your Problem-Solving Skills:In your application, don't just list your skills—show us how you've used them to solve real problems. Whether it's through past projects or work experiences, we love to see examples of your critical thinking and creativity in action.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our team at StudySmarter!
How to prepare for a job interview at Travtus
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, prompt engineering, and agent-based systems. Be ready to discuss your past experiences in designing and deploying these technologies, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Collaboration Skills
Since this role involves working closely with both platform and product engineers, be prepared to share examples of how you've successfully collaborated across teams in the past. Highlight your communication skills and how you ensure everyone is on the same page.
✨Demonstrate Problem-Solving Abilities
Expect to face some technical questions or scenarios during the interview. Think about how you can showcase your problem-solving skills by discussing specific instances where you've tackled complex issues in AI development or system integration.
✨Prepare Questions About the Role
Interviews are a two-way street! Prepare insightful questions about the company's AI platform, their current projects, and how they envision the future of AI at Travtus. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
