Job Description
Software Engineering Tech Lead – AI Systems (Remote / Hybrid)
£100,000 - £130,000 + Package
AI Connect are hiring a Software Engineering Tech Lead to lead the development of next-generation Digital Assistant and AI platforms. You’ll play a key role in shaping scalable, high-performance systems that support customer and colleague experiences across the organisation.
This is a hands-on technical leadership role focused on building resilient, enterprise-grade applications combining modern software engineering practices with emerging AI and conversational technologies.
What You’ll Do
* Design, build, and deploy high-performance, scalable applications and APIs that power digital assistant and AI-driven experiences.
* Lead the development of robust microservices and reusable platform components used across the organisation.
* Contribute to the architecture and delivery of AI-powered and conversational systems, including chat and agent-based workflows.
* Work with teams building LLM-enabled applications, integrating models such as OpenAI, Claude, and Gemini via APIs.
* Drive engineering best practices across scalability, resilience, testing, CI/CD, and system performance.
* Mentor engineering teams and help shape technical strategy across multiple initiatives.
* Collaborate closely with product, platform, and AI teams to deliver secure, enterprise-ready solutions.
Key Skills & Experience
* Strong background in software engineering and architecture, particularly within microservices or SOA environments.
* Proven experience leading software engineering teams and driving technical delivery.
* Strong hands-on development experience with Python or NodeJS.
* Experience designing and building full-stack or API-driven applications, ideally within conversational AI or chat-based environments.
* Experience working with cloud platforms such as AWS and containerised environments.
* Strong understanding of CI/CD pipelines, automated testing, scalability, and high-availability systems.
* Experience building or integrating AI-powered applications, including LLM APIs, agentic workflows, or RAG systems, is highly advantageous.
* Strong understanding of engineering best practices, system design, and performance optimisation.