Machine Learning Engineering Director

Jobtailor; California (MO); On-site; USD 180,000 - 270,000; Full time

Job summary

Jobtailor seeks aSenior Engineering Manager to lead vision, architecture, and delivery across Azure and AWS. You will coach engineering managers and senior staff while establishing standards and governance.

You will drive secure, scalable AI adoption, align with product, risk, and security stakeholders, and ensure Agile practices with disciplined delivery and Jira governance.

Qualifications

• Bachelor's degree or equivalent work experience.
• 10+ years of software engineering experience.
• 6+ years leading multiple software engineering teams.
• Minimum 5 years managing engineering teams, incl. managers.
• 10+ years 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 LLMs and RAG architectures.
• Familiarity with MLOps, CI/CD concepts for models, monitoring, and lifecycle considerations.
• Experience implementing enterprise-grade security, compliance, and data governance.
• Demonstrated ability to influence and partner with senior leadership.

Responsibilities

• Lead vision, architecture, roadmap, and technical leadership across multiple engineering teams.
• Own cloud-native platform design and delivery across Azure and AWS.
• Ensure alignment with security, data privacy, compliance, and Responsible AI practices.
• Drive cross-functional collaboration with product, risk, security, and stakeholders.
• Review designs, code, and architectural decisions to mitigate risks.
• Ensure Agile practices with sprint planning, backlog refinement, and delivery tracking.
• Enforce operational rigor with Jira artifacts kept current and prioritized.
• Provide feedback on team performance, resource allocation, and effectiveness.
• Manage HR-related matters, employee development, and team engagement.
• Ensure continuity of delivery with backup planning and absences coverage.
• Oversee timesheets and compliance with enterprise processes.

Skills

Technical leadership

Cloud platforms

Distributed systems

AI/ML familiarity

Security & compliance

Stakeholder collaboration

Education

Bachelor's degree or equivalent

Tools

Azure

AWS

MLOps

Job description

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.
• 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.