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.
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.
Ensure continuity of delivery through appropriate backup coverage, resource planning, and support during team member absences.
Oversee administrative responsibilities such as time tracking and compliance with enterprise processes (e.g., timesheets, reporting).
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.
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).
Working knowledge of AI/ML and GenAI concepts, including familiarity with LLMs, RAG architectures, and AI application integration (deep specialization not required).
Familiarity with MLOps practices, including CI/CD concepts for models, monitoring, and lifecycle considerations.
Experience implementing enterprise‑grade security, compliance, and data governance frameworks.
Demonstrated ability to influence and partner with senior technology and business leadership.