About the Project
The platform uses AI agent architectures to generate and validate educational content at scale, serving multiple products across the organization. The team owns the end-to-end lifecycle: workflow design, LLM orchestration, evaluation, and production operations.

About the Role
We are looking for a senior AI engineer ready to work at the heart of production AI systems. You will  contribute directly to two core services: Conversation Brain, an LLM-driven conversation engine, and  Ambient ORA, a speech assessment engine powering multiple products. The role sits at the intersection of product engineering and AI science, bridging research outputs from the R&D team into production-grade services.

Key Responsibilities:

• Design, develop, and optimize AI-driven content generation workflows.
• Contribute directly to our codebases, building and maintaining agentic workflows using Python (FastAPI, CrewAI, LangGraph, LangChain) and Go where needed.
• Build and maintain agentic workflows using CrewAI, LangGraph, and LangChain.
• Ensure code quality through unit and integration tests written as part of the development workflow, in line with our shift-left approach where developers own test creation.
• Operationalize AI models in collaboration with the AI R&D.
• Implement LLM observability and evaluation using Langfuse, OpenLit, and New Relic.
• Design and run LLM evaluation benchmarks and regression detection.
• Integrate and manage resources across Azure (Container Apps, Service Bus, Blob Storage) and AWS.
• Ensure robust CI/CD pipelines and contribute to SDLC best practices.
• Package, deploy, and scale applications using Docker; Kubernetes experience is a plus.

Required Skills & Qualifications

• Strong Python development skills (FastAPI) and hands-on experience with agentic and LLM frameworks 
  (CrewAI, LangGraph, LangChain, or equivalent).
• Production experience with LLMs, including prompt engineering, model evaluation, and 
  operationalizing research outputs into production services (Azure OpenAI, Google Vertex AI).
• Practical experience with Azure services (Container Apps, Service Bus, Key Vault, Blob Storage) and 
  familiarity with AWS.
• Experience with LLM observability and monitoring tools (Langfuse, OpenLit, New Relic, or equivalent).
• Solid grasp of CI/CD, DevOps, and SDLC. Working knowledge of Docker, with k8s experience as a plus.
• Familiarity with ML/NLP tooling (PyTorch, Hugging Face Transformers, spaCy, scikit-learn) a strong plus.
• Daily user of AI development tools (Cursor, Claude Code, Copilot).
• Fluent English, spoken and written.
• Nice to have: Working knowledge of Go, with the ability to read, modify, and maintain existing Go 
  services

Benefits:

• Opportunities for certification and training
• Dual monitor setup and high-spec workstations
• English courses
• Gym allowance
• Medical Reimbursement
• Full salary covered up to 20 days of sickness
• Flexible working hours
• Loyalty scheme
• Team building activities, special events and conferences
• UK/EU Travel opportunities
• Snacks and drinks in the office