Engineering Manager - AI Services and Solutions

The Engineering AI Team Lead owns the technical delivery of AI solutions, ensuring they are robust, scalable, and production-ready. This role blends leadership, hands-on engineering, and architectural oversight. You will mentor engineers and data scientists, set technical standards, and ensure that product requirements are translated into reliable solutions. Beyond delivery, you will help scale AI adoption across the firm by building engineering patterns, reusable services, and blueprints to drive adoption and scale AI across the firm.

Engineering Coordination & Development

• 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.

• Bachelor's or Master's in Computer Science, Machine Learning, or related field.
• 5+ years in AI/ML engineering, with 2+ years in a leadership role.
• Strong programming in Python and proficiency with ML frameworks (PyTorch, TensorFlow).
• Hands-on expertise in Azure AI/ML services (Azure ML, Azure DevOps, AKS).
• Practical experience with GenAI/LLMs (prompt engineering, RAG basics).
• Proven delivery across the full AI lifecycle: experimentation deployment monitoring.
• Strong communication and leadership skills in cross-functional environments.