Software Engineering Team Lead

Software Engineering Tech Lead – AI Systems (Remote / Hybrid)

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.

• 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.

• 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.