Lead Python Full-Stack Engineer (AI Integration)

We’re looking for aLead Python Full-Stack Engineer (AI Integration) to join our team in the United Kingdom in a hybrid working mode. In this role, you willlead the design and delivery of enterprise-grade solutions, combining backend development, modern front-end capabilities and AI/ML integrations in a cloud-native environment. You will drive architectural decisions, enforce engineering best practices and provide technical guidance on critical design aspects while contributing to complex engineering tasks.

Responsibilities

• Drive architecture decisions and define full-stack solution design in alignment with project goals
• Lead end-to-end development of scalable Python-based backend services and RESTful/GraphQL APIs
• Oversee implementation of modern front-end interfaces using React.js and TypeScript
• Integrate AI/ML and GenAI capabilities (LLM-based solutions) into production applications
• Ensure adherence to coding standards, testing strategy and CI/CD practices for high-quality releases
• Collaborate with stakeholders and cross-functional teams to deliver technical roadmaps and milestones
• Guide DevOps integration for containerization and deployment on Microsoft Azure
• Optimize application architecture for performance, scalability, and security in a cloud-native context

Requirements

• Minimum 5+ years of professional experience in software engineering with a focus on backend and full-stack development
• Strong proficiency in Python and frameworks such as FastAPI, Flask or Django
• Hands-on leadership experience in guiding full-stack delivery and architecture decisions
• Expertise in React.js and TypeScript for building modern user interfaces
• Working knowledge of GenAI and AI/ML model integration such as Azure OpenAI, LangChain
• Practical experience with CI/CD pipelines (GitHub Actions preferred)
• Deployment experience on Microsoft Azure, including containerized solutions with Docker
• Strong understanding of SQL databases (Microsoft SQL Server or equivalent) and NoSQL concepts
• Familiarity with microservices, API-first architecture and DevOps principles

Nice to have

• Knowledge of Azure AI Foundry, MLOps workflows and observability for AI models
• Hands-on experience with Databricks for data processing in analytics-driven solutions
• Understanding of RAG architectures, vector databases and advanced conversational AI patterns
• Familiarity with tools for documentation and developer productivity such as dbt (data build tool) and MKDocs
• Previous experience in energy, financial or utilities domains