AI Lead Developer

• Define and guide the technical direction for your squad, taking ownership of key architectural decisions, mitigating technical risks, and representing engineering in Architecture Review Board discussions.
• Lead the development of AI-driven products by designing and implementing LLM workflows, RAG pipelines, and agent-based features that operate reliably in production at scale.
• Champion the adoption of AI-assisted development tools across the entire software development lifecycle—from initial planning and design to code reviews, testing, and deployment—while setting high standards for engineering practices within the team.
• Build and deliver high-quality, production-ready solutions across the full stack, including backend systems in Node.js or Python, event-driven architectures on AWS, and frontend components using React when required.
• Support the growth of engineers across AI and full-stack areas through mentorship, code reviews, architectural discussions, and hands-on collaboration.
• Work closely with platform teams to leverage shared capabilities and contribute reusable solutions, avoiding unnecessary duplication and encouraging consistency across systems.
• Ensure that all delivered solutions are designed with compliance in mind, fully auditable, and aligned with the standards required for software in FCA-regulated financial environments.

• An experienced engineer with over 10 years in the field, including substantial experience building and maintaining AI/ML systems in production environments.
• Demonstrated technical leadership, with a track record of setting direction, making architectural decisions, mentoring team members, and shaping how engineering teams operate.
• Strong hands-on expertise with AI and LLM technologies, including prompt engineering, RAG architectures, model evaluation, and agent frameworks, with practical production experience.
• Deep proficiency in either Node.js or Python, along with solid working knowledge of the other, and the flexibility to choose the right tool for each problem.
• Strong experience with cloud-native development on AWS, including serverless and event-driven architectures and a focus on building scalable, maintainable systems.
• A proactive interest in emerging AI trends, combined with the ability to critically evaluate and adopt the most relevant technologies.

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