Data Science and AI Engineering Lead, VP

Driving the creation of new AI solutions for Chief Strategy & Innovation Office (CSIO).

We are seeking an AI Engineer with more than 18+ years of experience who will stand at the forefront of innovation, architecting, developing, and deploying groundbreaking AI solutions that redefine what's possible. We are seeking a visionary and highly motivated Engineer eager to leverage advanced AI models and platforms to conquer complex business challenges and accelerate digital transformation.

As a variety of data and AI development tools become more accessible, we are seeking an experienced Data Scientist and AI Engineer to help drive the implementation and delivery of AI strategy.

The role holder will be expected to lead the design, development, and implementation of new AI solutions for stakeholders. These solutions will vary in terms of complexity, but all will have the goal of simplifying and accelerating operations and controls activities, achieving cost save targets, and driving revenue growth.

Your key responsibilities:

• Help lead and develop a high-performing Data Science and AI Engineering team.
• Help drive the adoption of AI and analytics best practice across CSIO, IT (TDI), and the wider organization.
• Foster a collaborative and innovative team environment, encouraging continuous learning and skill development on topics across AI.
• Stay abreast of industry trends and emerging technologies in data warehousing, business intelligence, and cloud analytics, particularly within the Google Cloud Platform ecosystem.
• Conduct performance reviews, provide constructive feedback, and support career progression for team members as needed.
• Help ensure the CBIBOC Data Science and AI Engineering book of work is transparently documented and managed to ensure tasks are efficiently allocated and executed, and progress is easily tracked and reported.
• Ensure AI governance requirements, as mandated by policy, regulation, or law, are adhered to for all new solutions developed.
• Provide demos of new solutions, training materials, slides, and other materials as required to support the CBIBOC communication and upskilling agenda.
• Lead by example, working with other squad members to design, develop, and implement novel AI solutions.
• Partner with business stakeholders and other squad members to understand their needs and priorities, and identify new opportunities for the development or use of AI solutions.
• Ensure new AI use cases (squad projects) are rigorously evaluated and prioritized based on expected ROI, strategic alignment, technical feasibility, and risk.
• Ensure all new AI solutions are thoroughly tested, validated, controlled (e.g. implementation of guardrails, access permissions, etc.), and monitored on an ongoing basis.
• Ensure all new AI solutions are recorded in a centralized inventory and brought through the required approval steps prior to production implementation.
• Track against agreed KPIs to demonstrate the effectiveness and value of each AI solution (e.g. costs and benefits as well as accuracy, consistency, and performance).

Your skills and experience:

• End-to-end AI architecture and leadership: Lead the design, architecture, and implementation of highly scalable and robust AI-powered applications and services utilizing Python, FastAPI/Flask, FastMcp, LangGraph, ADK, and Google VertexAI.
• Advanced model integration and optimization: Architect, integrate, and expertly fine-tune large language models, with a strategic focus on the Gemini model, for advanced tasks and cutting-edge generative AI applications.
• Demonstrable experience using Data Science / AI developer tools and platforms such as GitHub, VS Code, PyTorch, TensorFlow, scikit-learn, MLflow, Weights and Biases, Jupyter Notebook, Hugging Face, LangChain, LangGraph, Google Vertex, Neo4j, etc.
• Experience with front-to-back AI solution design and architecture, particularly the design of agentic AI solutions.
• API architecture and integration: Drive the design and implementation of seamless API architectures and integrations with diverse internal and external systems, ensuring optimal data flow and functionality across the enterprise.
• Cloud infrastructure leadership: Lead the deployment, management, and optimization of AI solutions on cloud platforms, leveraging services like GCP Cloud Run/GKE, BigQuery, Cloud Composer, and CloudSQL for resilient data processing and infrastructure management.
• Code quality and AIOps governance: Establish and enforce rigorous code quality standards and best practices for software development and AIOps, ensuring clean, maintainable, and well-documented code across all AI projects.
• Advanced testing and deployment oversight: Architect and execute comprehensive test strategies for AI solutions, leading the deployment and continuous monitoring of models in production environments, ensuring high performance and reliability.
• Research and innovation leadership: Actively lead research into the latest advancements in AI, machine learning, and natural language processing, translating cutting-edge developments into innovative solutions and strategic initiatives.
• Cross-functional strategic partnership: Collaborate closely with product managers, data scientists, and other engineering leaders to define strategy, align priorities, and ensure the successful delivery of high-quality, impactful AI products that meet business objectives.
• Demonstrable experience with data / feature engineering, data product creation, and modern data solutions such as BigQuery, Looker, PostgreSQL, Pinecone, Spark, MongoDB, Redis, Databricks, Denodo, Snowflake, etc.
• Strong knowledge of current best practice for AI risk management across the solution lifecycle, and how to leverage technology to implement these controls (e.g. from development, testing, and validation of new solutions to setting access controls/permissions, implementing guardrails, and automating performance monitoring and reporting / dashboards).
• Ability to write / review Python code and experience using AI coding assistants (Claude Code, GitHub Copilot, etc.). SQL and Java experience desirable but not essential.
• Experience developing production-grade software within a Software Development Lifecycle (SDLC) control framework.
• The ability to balance people management, hands-on development work, and governance activities in a flexible day-to-day manner.
• The desire to grow and learn, keep up with the latest developments and new AI offerings emerging across the industry, and progress their Data Science / AI career.
• Proven ability to leverage AI tools to enhance productivity, optimize workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.

How we'll support you:

Training and development to help you excel in your career.

Coaching and support from experts in your team.

A culture of continuous learning to aid the progression of your career.

A range of flexible benefits that you can tailor to suit your needs.