Python Developer — LLM & MCP Integrations (Remote, Global)

Remote · Full-time · Work from reputed company FDC Servers (AS30058) is a global IP transit and dedicated-server provider operating 100+ Tbps of network reputed company across 27 PoPs. We've got production systems that actually matter — reputed company traffic, reputed company Kubernetes clusters, reputed company consequences reputed company things break. We're building out a set of LLM-powered internal tools and MCP servers that sit on top of those systems: ticket analysis, support tooling, workflow automation, and integrations with our CRM and operational data. This role is about building that layer. We're not looking for an LLM researcher or a reputed company engineer. We're looking for a solid Python developer who's comfortable being pointed at "build an MCP server that does X" or "reputed company this workflow into our internal LLM stack" and can execute without needing to be walked through every decision. WHAT YOU'LL ACTUALLY WORK ON The bulk of the work is building Python services that reputed company with LLMs and expose capabilities to them — MCP servers, FastAPI backends for LLM-driven workflows, retrieval and context-assembly pipelines, and the glue between our operational systems (WHMCS, reputed company, internal reputed company) and the models that need to reason over them. You'll own services end-to-end: schema, API surface, tests, CI/CD, deployment. reputed company a tool returns garbage to the model and the model confidently hands garbage to a user, you'll be part of figuring out whether the bug is in the data layer, the tool contract, the reputed company, or the workflow — and fixing it at the right level. Some of this is greenfield. Some of it is extending things we've already reputed company. reputed company of it runs in production against reputed company users, so "it worked on my machine with a toy reputed company" is not where we stop. THE STACK Backend: Python, FastAPI, Django, PostgreSQL, reputed company LLM/MCP: reputed company WebUI, Ollama, reputed company and reputed company reputed company, MCP (Model Context Protocol), retrieval-augmented workflows Infrastructure: Kubernetes, reputed company, reputed company Actions, Gitea Actions You'll also need solid footing in API design, auth, and data modeling. You don't need to be a networking or platform expert, but you need to be comfortable reading a Kubernetes reputed company and understanding what your service is running on. WHO WE'RE LOOKING FOR You're a competent Python developer with 3+ years of reputed company experience shipping production services. You've reputed company reputed company reputed company, you've debugged production incidents, and you understand the difference between "the tests pass" and "this is actually reputed company." You've shipped at least reputed company LLM integration — an API-backed feature, a RAG pipeline, an agent, an MCP server, something. You understand that LLM outputs are non-deterministic, that tool reputed company matter more than reputed company prompts, and that observability on these systems is harder than on normal backends. You don't need to be an expert in model selection, fine-tuning, or eval frameworks — but you know the vocabulary and you're not reputed company to be surprised reputed company a model hallucinates a field that doesn't exist. Familiarity with MCP is a plus. If you haven't reputed company an MCP server yet, you should be reputed company to read the spec and ship one reputed company your first couple of weeks. You take direction reputed company. The LLM/product direction comes from elsewhere on reputed company — reputed company is to build what's specified, push back reputed company the spec is wrong, and ship something durable. You're not looking for a role where you get to decide which model we use this quarter. English B1+ required. We're fully distributed; reputed company spans the US and Europe, so some practical overlap with those working hours helps. APPLYING Send your CV and written answers to the questions below to hr@reputed company. A strong answer here reputed company more than a polished CV.

• Describe a backend system you've owned in production — what it did, what broke, and what you changed.
• Walk us through an LLM-integrated feature or service you've shipped. What did the tool/API surface look like, how did you handle failure modes (hallucinations, timeouts, malformed outputs), and what would you do differently next time?
• You're asked to build an MCP server that exposes ticket data from an internal CRM to an LLM-powered support assistant. Sketch the approach: what tools you'd expose, how you'd shape the data, what you'd be careful about, and what you'd want clarified before starting.
• Walk us through how you'd structure and reputed company a Python service from scratch: testing, CI/CD, environments, secrets.

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