Job at a glance
Be more proactive, using information to identify new opportunities, and getting to them before our competitors. Realize cost savings, finding ways to make processes more efficient, enabling our people to focus on using their skills to further add business value. This team is working to transform the way in which we do business and to enable us to effectively leverage the latest AI advancements to our competitive advantage.
The Data Science & AI Delivery Lead is a key leadership role within this team, acting as the deputy to the Head of Data Science & AI Delivery and ensuring the smooth day-to-day running of AI delivery operations. The Data Science & AI Delivery Lead is the technical delivery leader for AI, machine learning, and advanced analytics solutions. This role owns technical execution, engineering standards, solution architecture, deployment quality, and production delivery of AI capabilities.
This role focuses on how solutions are designed, built, deployed, and scaled. What will you do in this role? The Data Science & AI Delivery Lead acts as the right hand to the Head of Data Science & AI Delivery, taking ownership of the day-to-day execution and coordination of data science and AI delivery across strategic projects and standalone use cases. You will play a hands-on leadership role - driving technical delivery, managing workstreams, and stepping in for the Head of when required.
This is not a purely managerial role. You will be expected to work directly in the codebase, review and shape technical designs, and maintain deep fluency with the tools and techniques the team uses daily. Working closely with the Head of, you will ensure projects are delivered to a high standard, on time, and with strong stakeholder engagement. In this role you will be responsible for: Day-to-Day Delivery Leadership: Own the operational running of AI delivery workstreams, ensuring the team is focused, unblocked, and delivering against priorities.
Act as the primary point of escalation when the Head of is unavailable. Own technical execution across all AI delivery workstreams. Lead architectural decisions, technical design reviews, implementation approaches, and production readiness reviews. Establish engineering standards, patterns, reusable frameworks, and delivery best practices. Project Management: Own technical delivery accountability from concept through production.
Ensure solutions meet security, governance, scalability, explainability, and operational support standards. Technical Oversight & Contribution: Provide technical guidance on solution design, model selection, and architecture decisions, ensuring the team is taking the right approach for each use case. Review code and technical outputs to maintain quality standards and contribute hands-on to Python-based development when needed, particularly during critical delivery phases or proof-of-concept work.
Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search). Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions for performance and drift. Champion engineering best practices across the team, including code review standards, documentation, version control (Git), and a clear separation between experimentation and production-ready code.
Technical Strategy & Architecture: Own AI solution architecture and technical design standards. Define engineering approaches for LLM applications, agentic systems, machine learning solutions, and AI platforms. Lead evaluation of emerging AI technologies and determine appropriate adoption. Establish standards for MLOps, AI observability, model lifecycle management, and responsible AI implementation.
Collaboration: Work closely with AXIS's Business Technology Solutions for solution architecture and delivery, and with the Program Office for pl