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

Company Background

Our client is a global leader in access solutions and smart home technologies. With over a decade of innovation in the IoT space, the company is a pioneer in connected home solutions, including garage door openers, gate systems, and smart access management tools. One of their flagship innovations is the platform, which allows users to control and monitor their home access systems through connected devices. The current focus is a mobile app designed to support and manage gated communities.

Project Description

AI platform is a modern, cloud-native, and device-integrated system supporting advanced computer vision, generative AI, and smart automation for access control and security. The platform is continuously evolving, with a strong focus on validation, automation, and scalability to support millions of IoT devices and next-generation smart home features.

Technologies

• Python
• FastAPI
• AWS
• Docker
• Kubernetes
• CI/CD
• LLM / Generative AI
• vLLM
• Kafka / RabbitMQ

What You'll Do

• Design and implement a rules engine platform as part of the AI microservices ecosystem;
• Collaborate with AI/ML engineers to integrate business logic and rule-based decisioning into the platform;
• Develop robust, maintainable, and scalable Python microservices;
• Ensure high code quality, test coverage, and adherence to best practices (PEP 8, code reviews, CI/CD);
• Work with containerization (Docker) and orchestration (Kubernetes) for deployment.

Job Requirements

• 4+ years of experience with Python;
• Experience building rules engines or similar business logic platforms;
• Experience with FastAPI or similar frameworks;
• Experience with Docker, Kubernetes, and CI/CD pipelines;
• Experience working with AWS (EKS, SQS, S3, EC2, MSK);
• Strong software engineering fundamentals and clean code practices;
• Basic experience with LLMs and tools like vLLM;
• Strong communication skills;
• English proficiency at B2 level or higher;

Nice to Have:

• Background in AI/ML platforms or agent frameworks;
• Familiarity with messaging systems (RabbitMQ, Kafka);
• Understanding of concurrent programming;
• Exposure to Amazon Bedrock;
• Familiarity with observability tools (OpenTelemetry, DataDog);

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.