Software Engineer Lead

Job Summary

This role is for a Lead Engineer (AI and Python) who wants to influence technical direction through strong engineering judgement and collaboration. You will technically lead a high impact AI engineering team and play a defining role in how AI driven software is built across a growing and ambitious organisation. This position comes with real ownership, where your technical judgement directly shapes outcomes.

You will work in close partnership with key business and technical stakeholders, collaborating to define cloud native, container first solutions designed for enterprise use from day one.

This is a hands-on technical leadership role. You will write production code, drive proof-of-concepts, and validate architectural decisions through implementation. Alongside this, you will set technical standards, guide design choices, and raise the bar for the team. You will also play a central role in hiring and building your team, reinforcing a strong engineering culture and a consistently high technical bar.

AI is central to the mission. You will operate at the intersection of exploratory AI development and enterprise grade engineering, turning emerging ideas into secure, scalable production systems. You will work alongside a friendly, collaborative team of high calibre engineers who take immense pride in their work, value good engineering practices, and support each other in building platforms and teams that underpin future capabilities.

Key Tasks & Responsibilities (Essential Functions)

• Lead the technical direction of a high impact AI engineering team, staying ‑hands-on‑ and setting the pace through example.
• Design and deliver cloud native, ‑container first‑ services that are built to scale and ready for real enterprise use.
• Partner closely with architects and key stakeholders to shape architecture, align on patterns, and translate strategy into practical engineering decisions.
• Take AI enabled capabilities from early exploration and proof‑-of‑-‑concept through to secure, reliable, production deployments.
• Write high-quality‑ Python code and help define the engineering bar for maintainability, testing, and operational excellence.
• Drive good engineering practices across code quality, CI/CD, containerisation, Kubernetes, and cloud operations, keeping teams focused on outcomes.
• Guide technical trade-offs and prioritisation, balancing innovation with pragmatism and ‑long-term platform health‑.
• Play a central role in hiring and onboarding, helping build a high calibre team and strengthening a collaborative, supportive culture‑.
• Mentor and coach engineers through reviews, pairing, and technical feedback, enabling growth and shared ownership.
• Stay current with fast‑moving AI and cloud technologies, assessing new approaches and introducing them where they add real value.

Skills and Minimum Experience Required

• Strong professional software engineering background. (Typically, 10+ years, but we value impact and evidence of delivery over a specific number.)
• Proven technical leadership in a delivery team, such as leading design discussions, setting technical direction within a team, mentoring engineers, and raising engineering standards through example.
• Strong Python engineering skills including maintainable OOP design, typing, asynchronous programming, and building robust service layers (FastAPI preferred).
• Demonstrated experience designing and building REST APIs and service integrations, with a focus on reliability, observability, and performance.
• Prior cloud experience is mandatory, with hands-on delivery on at least one hyperscaler (Azure preferred; AWS/GCP also valued).
• Container experience is essential, including packaging, running, and troubleshooting containerised services across environments.
• Kubernetes experience is highly preferred, including deploying, operating, and debugging services in a cluster (or strong motivation and evidence of learning it quickly if you have deep container/cloud experience).
• Experience with modern DevOps practices and CI/CD pipelines (e.g., GitHub Actions, ArgoCD, Azure DevOps) and pragmatic Git branching/release strategies.
• Strong quality mindset, including unit/integration testing (PyTest), code review habits, and an ability to balance delivery pace with engineering discipline.
• Solid understanding of security fundamentals for modern services, including AuthN/AuthZ (OpenID/OAuth2) and secure build/deploy practices (e.g., container scanning).
• Comfortable working in Agile environments (Scrum/Kanban; SAFe exposure helpful) and collaborating effectively across product, architecture, and data/AI stakeholders.
• Experience working with SQL and NoSQL data stores, including data modelling and operating services backed by document, key value‑, or similar relational (PostgreSQL preferred) and non‑relational databases.
• Solid core Linux skills, comfortable working in Linux environments for development, debugging, deployment, and operational troubleshooting.
  
  

Preferred Skills and Experience

• Experience building with Generative AI and/or Agentic AI frameworks and patterns (MAF, LangChain, LanghGraph, CrewAI, Hugging Face, OpenAI APIs, Claude Code), with a pragmatic approach to taking PoCs toward production readiness.
• Familiarity with event-driven architecture and scalable integration patterns across enterprise systems and IoT-adjacent environments.
• Azure platform depth (e.g. Resource Groups, VNETs, Cosmos DB, serverless, ...) and/or broader cloud platform engineering experience.
• DevSecOps experience, including code-to-cloud security practices and improving pipelines and guardrails without slowing teams down.
• Demonstrable interest in modern AI concepts (transformers/attention, deep learning foundations) and staying current in a fast-moving technical landscape.
• General knowledge of web application development, including familiarity with modern frontend frameworks and patterns. Exposure to React and/or Next.js is a plus.

Other

• Agile: Jira, Azure DevOps
• Collaboration: Confluence, Miro, Teams
• Development: Git, VSCode, Docker
• Testing: Postman, PyTest
• Cloud & DevOps: Azure, ArgoCD, GitHub Actions
  
  

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