AWS Senior Cloud & ML Engineering Associate Director

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an AWS Senior Cloud & ML Engineering Associate Director based in the United States.

This leadership opportunity is ideal for an experienced cloud and machine learning engineering professional ready to drive large-scale technology transformation. You will lead complex AWS engagements, designing secure, scalable, and production-ready cloud architectures that bridge data science innovation and real-world machine learning applications. Working closely with clients, data scientists, platform engineers, and technical leaders, you will turn business objectives into practical implementation strategies.

You will champion cloud security, automation, resilience, and operational excellence while developing reusable engineering standards and solutions. Beyond technical delivery, you will mentor engineering teams, strengthen strategic client relationships, and contribute to business growth. Join a collaborative, client-focused environment where emerging AI technologies and cloud innovation create opportunities for meaningful impact.

• Lead AWS cloud architecture and implementation:
  Own the architecture, technical direction, and delivery outcomes of complex cloud engineering engagements, translating business requirements into actionable implementation plans.
• Drive machine learning and AI integration:
  Bridge data science research and production-grade AWS deployments, enabling faster experimentation, reliable ML infrastructure, and scalable AI solutions.
• Design secure and resilient cloud environments:
  Make architecture decisions covering networking, identity and access management, security, automation, observability, resilience, compliance, and AWS Well-Architected principles.
• Oversee technical delivery and risk management:
  Manage critical dependencies, identify and mitigate technical risks, resolve complex engineering challenges, and ensure high-quality project outcomes.
• Develop cloud engineering standards:
  Create reusable reference architectures, implementation patterns, technical frameworks, and delivery standards to improve consistency, efficiency, and maintainability.
• Lead and mentor technical teams:
  Guide cloud engineers and cross-functional specialists, review architecture decisions and critical deliverables, and support professional development through coaching and knowledge sharing.
• Strengthen client relationships:
  Provide strategic technical guidance to client technology leaders, build trusted partnerships, and identify opportunities to improve cloud capabilities and address evolving business needs.
• Support business development:
  Contribute to client proposals, solution design, engagement scoping, and growth strategies while identifying relevant opportunities for additional services.
• Ensure operational readiness:
  Facilitate sustainable transitions to ongoing operations and continuously improve architecture, security, reliability, automation, and operating models.

• Education:
  
  Bachelor's degree in Management Information Systems, Information Systems, Computer Science, or a related discipline.
• Professional experience:
  At least seven years of experience in professional services or industry, including a minimum of five years of hands-on AWS experience across multiple service domains.
• Cloud architecture expertise:
  Strong experience designing and implementing AWS solutions across networking, identity, security, automation, resilience, observability, and cloud governance.
• Python development:
  Strong Python programming skills, with demonstrated ability to produce maintainable, reliable, production-quality code.
• Machine learning lifecycle:
  Familiarity with ML lifecycle and deployment tools such as Amazon Sage Maker, MLflow, or equivalent technologies.
• Agentic AI experience:
  Experience with agentic AI frameworks and managed agent runtimes, including Amazon Bedrock Agents, Agent Core, or comparable solutions.
• Cross-functional collaboration:
  
  Experience working alongside data science and platform engineering teams to move technical concepts and research into production-ready solutions.
• Required certifications: AWS Certified Solutions Architect
  - Associate and AWS Certified Generative AI Developer.
• Preferred certifications: AWS Certified Solutions Architect
  - Professional, AWS Certified Machine Learning
  - Specialty, or AWS Certified Dev Ops Engineer.
• Technical leadership:
  Demonstrated ability to guide…