Director, Enterprise AI Platform Architect

Accountabilities Partner with technology and product teams to identify and prioritize agentic AI opportunities that align with product roadmaps and business objectives.

Lead end-to-end delivery of AI agent solutions, using rapid development approaches to achieve MVPs and measurable proof-of-value outcomes within compressed timelines.

Guide AI solutions from prototype through production deployment, helping teams establish scalable and reliable operating models.

Conduct AI maturity assessments, identify capability gaps, and develop tailored roadmaps for improvement.

Perform architectural reviews and recommend improvements related to performance, scalability, security, resilience, and maintainability.

Design enterprise AI platforms across AWS, Azure, and GCP, using appropriate abstraction layers to support vendor independence.

Develop and maintain reference architectures covering generative AI applications, agentic systems, and multi-agent collaboration patterns.

Establish appropriate autonomy and human-in-the-loop controls based on risk, regulatory requirements, and business context.

Define standards for AI development, deployment, monitoring, lifecycle management, privacy, model provenance, governance, and auditability.

Serve as a technical authority on generative AI, LLMs, RAG, autonomous agents, and multi-agent architectures.

Evaluate emerging AI technologies and assess their potential impact on product strategies, technology roadmaps, and investment priorities.

Develop and promote reusable AI platform design, development, and deployment practices across multiple organizations.

Support technical due diligence by assessing AI capabilities, technical debt, architecture, and readiness for agentic AI adoption.

Translate complex technical findings into clear recommendations for executives, technology leaders, and other stakeholders.

Collaborate across multiple companies and teams simultaneously while maintaining strong delivery focus and technical quality.

Requirements

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical discipline.

At least 3 years of experience in AI/ML platform architecture and development, including 2+ years of recent hands-on experience with generative AI and agentic architectures in production applications.

Demonstrated success delivering AI applications into production environments rather than limiting work to prototypes or research.

Strong expertise in generative AI technologies, including LLMs, RAG architectures, diffusion models, prompt engineering, and model fine-tuning.

Deep understanding of agentic architectures, autonomous agents, multi-agent systems, and enterprise AI application patterns.

Strong knowledge of public cloud AI services across AWS, Azure, and GCP, with the ability to design secure, scalable, and vendor-agnostic platforms.

Solid foundations in machine learning and deep learning, as well as AI model development, deployment, and lifecycle management.

Experience designing platform abstraction layers and architectures that avoid unnecessary vendor dependency.

Ability to operate effectively in fast-paced, ambiguous environments and deliver proof-of-value solutions on compressed timelines.

Strong analytical, problem-solving, and architectural decision-making skills.

Excellent communication, presentation, and interpersonal skills, with the ability to explain sophisticated technical concepts to executive audiences.

Experience working in private equity portfolio companies, consulting, or other multi-client environments is strongly preferred.

Benefits

Annualized base salary range of $200,000–$315,000 , depending on experience, expertise, geographic location, and skill set.

Potential eligibility for an annual cash bonus.

Comprehensive employee benefits package.

Opportunity to work on enterprise-scale AI transformation initiatives across a diverse portfolio of organizations.

Hands-on exposure to emerging generative AI, agentic AI, and multi-agent technologies.

High-impact environment combining technical architecture, innovation, strategic advisory, and production delivery.

Remote work environment.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

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