- Coordinate and develop within a high-performing team of AI engineers and data scientists.
- Foster a culture of inclusion, continuous learning, and technical excellence.
Technical Strategy & Execution
- Define the engineering approach and architecture for AI solutions and services.
- Evaluate and adopt the right tools and frameworks to meet product requirements.
- Ensure solutions are designed for scalability, security, and maintainability.
Project Delivery
- Translate product requirements into technical deliverables.
- Manage planning, resourcing, and execution of engineering work on Azure.
- Oversee delivery quality, risk management, and timelines.
Hands-On Engineering
- Contribute to architecture and code reviews, and resolve complex technical challenges.
- Build and optimize ML pipelines, reusable services, deployment workflows, and MLOps/DevOps automation.
- Stay up to date with ML, GenAI, and infrastructure best practices.
Governance & Best Practices
- Define coding standards, CI/CD pipelines, testing protocols, and documentation.
- Ensure compliance with privacy, security, and responsible AI guidelines.
- Promote operational reliability and maintainability.
Enablement & Adoption
- Develop engineering services, patterns, and blueprints to drive adoption and scale AI across the firm.
- Share technical knowledge through documentation, training, and community-building.
- Enable reusability and consistency of AI solutions across teams.