AI Engineering Team Leader

About the Role The AI Team Leader is responsible for leading Titan's AI Engineering function and driving the development of AI-powered capabilities across the Titan DMS platform.

Reporting to the Engineering Manager, this role provides technical leadership across AI architecture, Generative AI, LLM integration, AI Agents, and intelligent automation. Working closely with Product, Engineering, UX, and Business stakeholders, the AI Team Leader will define Titan's AI roadmap, establish engineering standards, and deliver scalable, secure, and production-ready AI solutions integrated into Titan's.NET ecosystem.

Key Responsibilities Leadership & Team Management

Accountable for the successful planning, prioritisation and delivery of the AI Engineering team's work. Provide technical leadership across AI initiatives. Assess emerging AI technologies and industry trends to inform Titan's long-term AI strategy. Define and maintain Titan's AI architecture to ensure scalable, secure and maintainable integration with existing platforms. Establish AI engineering standards and development best practices. Lead cross-functional AI initiatives that support Titan's strategic objectives. Lead, mentor and develop the AI Engineering team. Manage team performance, technical capability, development and resource planning. Participate in recruitment, interviewing and onboarding of AI Engineering team members. Promote knowledge sharing and continuous learning. AI Product Development

Partner with Product Managers to define, prioritise and maintain Titan's AI product roadmap, ensuring initiatives are aligned to customer value, technical feasibility and commercial impact. Evaluate and recommend AI platforms, models and tooling to optimise quality, performance and cost. Lead the development of AI-powered capabilities across the Titan DMS platform. Design and integrate AI solutions into existing C#/.NET and WinForms applications. Lead the development of modern web applications using React, Angular or similar frameworks. Drive implementation of LLMs, AI Agents, Prompt Engineering, and workflow automation. Design RAG and knowledge retrieval solutions. AI Strategy & Governance

Establish AI governance, evaluation frameworks, and quality standards. Drive AI security, monitoring, observability, and continuous improvement. Develop reusable AI components, frameworks, and reference architectures. Ensure AI solutions comply with Titan's secure software development standards, SOC 2 Type II controls and applicable privacy requirements. Establish policies for responsible AI development and deployment. Manage AI-related risks including hallucination, bias, privacy and model drift. Stakeholder Collaboration

Build strong partnerships with Product, Engineering, UX and Business stakeholders to ensure successful delivery of AI initiatives. Translate business requirements into AI solutions. Provide expert technical advice to Product and Engineering teams throughout solution delivery. Financial Accountability

Contribute to AI technology planning and budget recommendations, ensuring efficient use of AI platforms and services. Skills, Qualifications & Experience Minimum 7 years' software engineering experience. Strong experience with C#/.NET application development. Strong experience with modern web applications development using React, Angular or similar frameworks. Experience designing and delivering LLM / Generative AI solutions in production. Experience integrating AI capabilities into enterprise or SaaS products. Experience with AI Agents, Prompt Engineering, and RAG. Strong understanding of REST APIs, distributed systems, and software architecture. Experience working with AWS cloud services and designing cloud-native AI solutions. Experience leading engineering teams or technical initiatives. Excellent stakeholder management and English communication skills. Preferred

Experience with Amazon Bedrock, Anthropic Claude, OpenAI API, or similar AI platforms. Experience with AWS AI services. Experience with vector databases and AI evaluation frameworks. Experience with AI governance, security, and Responsible AI. Experience building AI capabilities for SaaS products. Key Success Measures

Successful delivery of Titan's AI roadmap and AI-powered product capabilities. Delivery of high-quality, scalable, secure and reliable AI solutions. Strong adoption and measurable business value from AI capabilities across Titan products. Effective leadership, engagement and capability development of the AI Engineering team. Continuous improvement in AI engineering standards, governance and best practices.