Senior Engineering Manager - Akamai Inference Cloud

About the Role

Day-to-day, the role entails driving technical strategy for model quality and safety, including guardrails, content filtering, red-teaming, and compliance enforcement. The Senior Engineering Manager will also be responsible for recruiting top talent, growing engineers in a rapidly evolving domain, and establishing engineering standards and best practices for responsible AI.

The AIC team is part of a larger ecosystem focused on cloud technology, and this role offers the opportunity to collaborate with platform, runtime, and developer experience teams to deliver seamless model lifecycle capabilities.

What You Will Do

• Build and scale a team of ML engineers focused on model validation, quantization, safety systems, and lifecycle automation
• Lead technical strategy for model quality and safety, including guardrails, content filtering, red-teaming, and compliance enforcement
• Drive model optimization initiatives spanning quantization, distillation, and inference performance tuning
• Own the model onboarding pipeline from security scanning and validation through optimization and production deployment
• Build and manage the bring-your-own-model pipeline, enabling customers to onboard, validate, optimize, and serve custom models with consistent quality and safety standards
• Establish engineering standards and best practices for responsible AI, model evaluation frameworks, and fine-tuning infrastructure
• Collaborate with platform, runtime, and developer experience teams to deliver seamless model lifecycle capabilities
• Develop and implement model lifecycle management processes
• Work closely with stakeholders to understand customer needs and adapt the team's strategy accordingly
• Foster a culture of innovation, experimentation, and continuous learning within the team

What We Are Looking For

• 10 years of relevant experience in building and scaling high-performing ML engineering teams
• Experience leading teams that shipped model lifecycle, model safety, or ML optimization products in production
• Hands-on understanding of model quantization, inference optimization, and serving frameworks such as vLLM, TensorRT, or Triton
• Expertise in responsible AI practices, including content safety, adversarial robustness, guardrail systems, and compliance frameworks
• Experience with LLM architectures, fine-tuning workflows, and model evaluation methodologies
• Proficiency with cloud-native technologies, including Kubernetes and distributed systems at a global scale
• Strong leadership and team management skills, with the ability to recruit, mentor, and grow engineers
• Excellent communication and collaboration skills to work effectively with cross-functional teams

Nice to Have

• Experience with large-scale model deployment and management
• Knowledge of edge computing and its applications in AI model deployment
• Familiarity with DevOps practices and tools for continuous integration and delivery
• Experience with agile development methodologies and version control systems like Git

Benefits and Perks

• The opportunity to work on cutting-edge AI and ML technologies
• Competitive compensation package
• Flexible working arrangements through Akamai's FlexBase program
• Comprehensive health insurance benefits
• Generous PTO and holiday policy
• Access to continuous learning and professional development opportunities
• Collaborative and dynamic work environment with a team of innovators
• Recognition and reward for outstanding performance and contributions

• Highlight your technical expertise: Make sure your resume and cover letter showcase your experience in ML engineering, model validation, and lifecycle management.
• Prepare to talk about responsible AI: Demonstrate your understanding of responsible AI practices, including content safety, adversarial robustness, and compliance frameworks.
• Showcase your leadership skills: As a Senior Engineering Manager, highlight your experience in leading teams, recruiting top talent, and fostering a culture of innovation.
• Emphasize your cloud-native skills: Proficiency in cloud-native technologies, such as Kubernetes and distributed systems, is crucial for this role.
• Be ready to discuss model optimization: Showcase your knowledge of model optimization techniques, including quantization, distillation, and inference performance tuning.
• Research Akamai's culture and values: Understand Akamai's commitment to innovation, flexibility, and responsible AI to show your enthusiasm for the company and role.
• Prepare questions for the interview: Come up with thoughtful questions about the team, the role, and the company's vision for AI and ML to demonstrate your interest and engagement.