Director, AI Architect

• Serve as a subject matter expert on generative AI, agents, and agentic
  architectures, providing thought leadership and strategic guidance to portfolio
  companies.
• Identify and evaluate emerging AI technologies and trends, assessing their
  potential impact on portfolio company product roadmaps.
• Develop and evangelize best practices for AI platform design, development, and
  deployment.

Portfolio Company Collaboration & Guidance:

• Partner with portfolio company technology and product teams to identify and
  prioritize AI opportunities.
• Provide hands-on guidance and support for the design and implementation of AI-
  powered solutions.
• Conduct architectural reviews and provide recommendations for optimizing AI
  platform performance, scalability, and security.
• Guide portfolio companies through the design considerations of agentic architectures.

AI Platform Architecture & Design:

• Design and implement scalable, resilient, and secure AI platforms leveraging
  public cloud AI services (AWS, Azure, GCP).
• Develop and maintain reference architectures for AI applications, including
  generative AI models and agentic systems.
• Define standards and best practices for AI model development, deployment, and
  monitoring.
• Ensure proper governance of AI platforms. 

Generative AI & Agentic Architectures:

• Lead the development and implementation of generative AI solutions, including
  large language models (LLMs) and other generative models.
• Design and implement agentic systems, incorporating autonomous agents and
  multi-agent collaboration.
• Evaluate and select appropriate generative AI and agentic frameworks and tools.
• Hands on experience with prompt engineering, and model fine tuning.

Cloud AI Capabilities:

• Maintain deep expertise in public cloud AI services, including machine learning
  platforms, generative AI APIs, and agentic frameworks.
• Evaluate and recommend appropriate cloud AI services for specific use cases.
• Optimize cloud AI deployments for cost-effectiveness and performance.

Implementation & Deployment:

• Provide hands-on support for the implementation and deployment of AI
  applications in production environments.
• Troubleshoot and resolve technical issues related to AI platform performance and
  scalability.
• Ensure seamless integration of AI solutions with existing portfolio company systems.

Due Diligence:

• Assist in the due diligence process of potential portfolio companies, assessing
  their AI technology and capabilities.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a
  related field.
• Minimum of 8+ years of experience in AI platform architecture and development.
• Deep expertise in generative AI, agents, and agentic architectures.
• Hands-on experience implementing AI applications in production environments.
• Strong understanding of public cloud AI services (AWS, Azure, GCP).
• Proven ability to design and implement scalable and resilient AI platforms.
• Excellent communication, presentation, and interpersonal skills.
• Experience with portfolio companies, or within a consulting environment is a plus.

Minimum of 8 years of experience in the following:

• Generative AI (LLMs, Diffusion Models, etc.)
• Agentic Architectures and Autonomous Agents
• Cloud AI Platforms (AWS, Azure, GCP)
• AI Model Development and Deployment
• AI Platform Architecture and Design
• Prompt Engineering
• Machine Learning and Deep Learning
• Problem-Solving and Analytical Skills
• Communication and Collaboration

The annualized base pay range for this role is expected to be between $250,000-300,000. Actual base pay could vary based on factors including but not limited to experience, subject matter expertise and the applicant's skill set. The base pay is just one component of the total compensation package for employees. Other rewards may include an annual cash bonus and a comprehensive benefits package.