Senior Software Engineer - AI
Job Description Senior Software Engineer – AI Native Platforms Function: Tech Location: Hybrid, London or Peterborough office Curious about what’s next? So are we. Join Compare the Market and help to make financial decision making a breeze for millions. At Compare the Market, we’re a purpose-driven business powered by tech and AI. We’re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers. We’ve carved a meerkat-shaped niche and we’re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you’ll fit right in. We’d love you to be part of our journey: As a Senior Software Engineer (AI Engineering), you’ll take a leading role in designing and implementing agent-ready systems and developer tools. You’ll build production-grade software that enables safe, scalable, and AI-augmented engineering, while mentoring and guiding engineers to raise the bar across the team. Some Of The Great Things You’ll Do
- Lead the design and development of services that support AI agent interaction
- Drive the application of GenAI to modernise, refactor, and accelerate legacy systems
- Define and implement APIs, contracts, and metadata aligned with the Model Context Protocol
- Shape and evolve internal tooling that supports AI-native SDLC workflows
- Influence architecture decisions, conduct design and code reviews, and lead incident response
- Proven backend development expertise, with experience delivering complex, high-scale systems
- Ability to mentor, guide, and upskill engineers within the team
- Familiarity with or eagerness to advance in:
- Model Context Protocol for managing context and tool interfaces for agents
- LLM integration patterns including prompt orchestration, multi-agent planning and tool calling
- Retrieval-Augmented Generation (RAG) for dynamic context injection
- Model selection / A/B testing / observability
- Delivers high-quality, maintainable code that meets business needs
- Takes ownership of complex problems end-to-end, from design through deployment
- Rapidly learns, applies, and advocates for emerging AI-native engineering patterns
- Raises the bar for technical excellence, system simplicity, and agent-readiness
- Actively contributes to the growth and effectiveness of the wider engineering team