LLM Backend Engineer

Job description

We’re building a new product from scratch - focused on pragmatic, production-ready LLM-based agents. The research and architecture phase is happening. Now we need engineers who will help turn those decisions into a real, scalable system. This is not about blindly playing with prompts. This is about building backend services, APIs, evaluation pipelines, and infrastructure that make agentic systems reliable in production. We’re tackling a real-world problem with a clear path to market, backed by SafeQ Cloud - and you’ll also help shape and improve the in-house tools that power the product. What you’ll actually work on: You won’t just receive tasks. You’ll participate in refinements and technical discussions - but the focus is clear: build it well and ship it. - Designing and implementing backend services (Python or .NET) - Integrating LLM vendors (OpenAI, Anthropic, Google…) - Working with LangChain stacks, evaluation tooling (e.g., DeepEval) - Building and tuning RAG pipelines, vector databases - Connecting (and building) MCP servers - Making sure what we build is testable, observable, and deployable - Helping evolve the architecture as we move from prototype to production Your tool...