Machine Learning Engineering Director

Key Responsibilities

• Lead the vision, architecture, roadmap, and provide technical leadership across multiple engineering teams; develop engineering managers and senior engineers while establishing standards, guardrails, and governance models.
• Own cloud-native platform design and delivery across Azure and AWS, ensuring scalability, reliability, performance, and cost optimization.
• Ensure alignment with enterprise requirements for security, data privacy, compliance, and Responsible AI practices.
• Drive cross-functional collaboration with product, risk, security, and business stakeholders to enable secure and scalable AI adoption.

Operational Leadership & Execution Discipline

• Maintain strong awareness of team delivery, technical issues, and platform risks; step in to review designs, code, and architectural decisions as needed.
• Ensure Agile practices are consistently followed, including sprint planning, backlog refinement, and delivery tracking.
• Enforce operational rigor across teams, including keeping Jira artifacts current, transparent, and aligned to priorities.
• Provide ongoing feedback on team performance, resource allocation, and organizational effectiveness to optimize delivery outcomes.
• Manage core people leadership responsibilities, including addressing HR-related matters, supporting employee development, and ensuring team engagement.
• Oversee administrative responsibilities such as time tracking and compliance with enterprise processes (e.g., timesheets, reporting).
• Continuously identify and drive improvements to increase team velocity, reduce friction, and accelerate platform delivery.

Basic Qualifications

• Bachelor's degree, or equivalent work experience
• 10 or more years of relevant software engineering experience
• Six or more years of experience leading multiple software engineering teams

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• Minimum 5 years of experience managing engineering teams, including direct oversight of engineering managers and senior technical staff
• 10+ years of experience in software engineering, platform engineering, or related disciplines
• Proven experience designing and delivering large-scale, distributed systems and cloud-native platforms (Azure and/or AWS)
• Familiarity with AI/ML and GenAI concepts, including familiarity with LLMs, RAG architectures, and AI application integration
• Experience implementing enterprise-grade security, compliance, and data governance frameworks
• Demonstrated ability to influence and partner with senior technology and business leadership

Preferred Qualifications

• Experience supporting or partnering on AI/ML or GenAI platform initiatives
• Familiarity with Responsible AI, model risk management, or regulatory considerations
• Experience with API-first platforms and event-driven architectures
• Background in financial services or other highly regulated industries
• Experience leading geographically distributed and multi-vendor engineering teams