Agentic AI Developer (Python)

About Us: ClearRoute is an engineering consultancy bridging Quality Engineering, Cloud Platforms and Developer Experience. We help enterprises reliably bring high-impact digital products to market faster, cheaper, and safer, working with technology leaders facing complex business challenges. We take as much pride in our people, culture and work-life balance as we do in making better software. We’re not just making better software. We’re making the making of software better. Collaborative, entrepreneurial and dedicated to problem solving, we bring the step change our customer need to sustain innovation. Our values challenge us to do the best we can for ClearRoute, our customers and most importantly our team. This is an opportunity for you to build the organisation from the ground up, use your voice to drive change and help transform organisations and problem domains. Role: Design and build the scalable service and API layer that powers an AI driven code modernisation and migration platform, combining agentic workflows with deep static analysis to automate the understanding, transformation, and migration of legacy systems at scale. Key Responsibilities: Design, build, and maintain scalable Python microservices and APIs that power and orchestrate agentic workflows in production Build and integrate MCP servers and tools, enabling agents to reliably discover, call, and chain external capabilities Own the full lifecycle of backend services supporting AI agents, ensuring they're robust, observable, well-tested, and production-ready at scale Actively shape agentic architecture decisions, from tool-calling patterns and orchestration strategies to state management and multi-agent coordination Required Skills & Experience: Strong Python engineering skills: writing clean, testable, production-grade code that holds up under real world load Proven experience designing and building microservices and RESTful APIs in production environments Solid grounding in software design principles and systems thinking, especially around distributed, event-driven, or asynchronous systems Genuine, hands-on interest in GenAI and agentic systems not just familiarity with the concepts, but active experimentation or delivery experience Practical experience with LLMs, agentic frameworks (e.g. LangGraph, CrewAI, or similar), or prompt engineering in real projects Direct experience with MCP, or comparable agent tool-serving and tool-calling patterns Working knowledge of Git workflow automation, and experience with GitHub/GitLab APIs for building developer tooling or automation Desirable Experience: Deep understanding of how agents consume, select, and reason about external tools and services Some exposure to frontend development or UI frameworks (React, Vue, or similar) for building agent-facing interfaces or observability dashboards Comfortable operating in a container-native environment (Kubernetes, Docker), including deploying and…