Forward Deployed Engineer
The Role
As a Forward Deployed Engineer at Cyclomedia, you are building the infrastructure that determines how an entire organisation uses AI - not maintaining it, not extending it, building it from the ground up. You are one of two FDEs on the AI Platform team, with a clear mandate: make it possible for every team in the company to deploy AI-powered tools in production, safely and at scale.
This is not a prototyping role. The decisions you make now will shape how Cyclomedia works with AI for years to come. You own the full stack: the shared app framework, the deploy pipeline, the agentic monitoring layer, and the data architecture that keeps the landscape coherent as it grows. In the next phase, you embed directly into business teams - identifying where AI can have the most impact and shipping production applications alongside the people who need them.
Key Responsibilities
Platform ownership: Design and own the shared infrastructure that lets anyone in the organisation deploy AI tools safely - without creating technical debt, security risk, or fragmentation.
Agentic monitoring: Build and operate the monitoring layer that keeps all deployed AI applications coherent, secure, and continuously improving - with you as the human in the loop when automated systems need judgment.
Data architecture: Maintain the schema registry and data architecture across all AI applications as the landscape scales. This becomes the foundation of Cyclomedia’s context layer to enable AI Agents.
Landscape stewardship: Catch duplication, integration opportunities, and emerging risk before they become problems. You are the person who keeps standards high as the platform grows.
Forward deployment: Once the platform foundation is in place, move into our internal teams directly - identify where AI adds the most value and build production applications alongside the people who need them.
Requirements
Full-stack engineering: You build and ship production software. You have strong instincts for scalable architecture, clean defaults, and avoiding future problems. Proficiency in Python and/or a modern backend framework is expected.
Agentic AI: Hands-on experience with agentic systems - multi-step reasoning, tool use, prompt engineering at production quality. Not toy projects.
AI-native mindset: You live and breathe AI - not as a spectator, but as someone who pulls the team forward. You follow what is real and what is hype, and you can tell the difference. You inspire the people around you with what is actually possible, while keeping a sharp eye on what is not ready yet. You do not chase every shiny thing, but you make sure the team never falls behind on the things that matter.
Infrastructure: Familiarity with cloud-native development (Azure stack), Docker, Kubernetes, Infrastructure as Code (IaC), and operating production systems at scale.
Security: You are not only comfortable, but are confident that you can secure resources, applications, and agents in complex cloud environments.
Judgment: You work with a high degree of autonomy in an ambiguous environment. You know when to move fast and when to be careful.
Nice to have: RAG pipelines, vector databases, AI-native application architectures. Familiarity with geospatial data, government/DOT customers, or enterprise software.