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About the role
Key responsibilities & impact- 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
- Work alongside platform engineers to define the APIs and services that agents consume and use
- Work closely 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 that enable 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 across engineering and product teams to translate business and technical goals into robust platform capabilities
Requirements
What you’ll need- 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.
Benefits
Comp & perks- Private Healthcare
- Pension
- Deliveroo Allowance
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
LLM-based applicationsprompt engineeringprompt tuningAPI designservice integrationworkflow controlmodel selectionend-to-end testingperformance optimisationsoftware engineering
Soft Skills
collaborationcommunicationproblem-solvingleadershipadaptabilitycreativitycritical thinkingattention to detailorganizational skillsinterpersonal skills