Lead Python Full-Stack Engineer (AI Integration)
We’re looking for a Lead Python Full-Stack Engineer (AI Integration) to join our team in the United Kingdom in a hybrid working mode. In this role, you will lead 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
