The Assistant Director – AI Solution Architect serves as both a technical leader and a business enabler. The role is responsible for designing, promoting, and delivering AI-focused infrastructure solutions for enterprise and government clients. It combines deep technical expertise with strong commercial understanding to support revenue growth and successful implementation of GPU-accelerated, AI-powered architectures.

The role works closely with internal teams and external technology partners to design secure, scalable, high-performance solutions supporting AI/ML, HPC, and data analytics across hybrid and multicloud environments.

Key Responsibilities

• Identify AI-related opportunities across enterprise sectors in coordination with Sales and Business Development.
• Lead client discussions to understand needs and translate them into AI-driven solution designs.
• Manage the technical sales cycle: presentations, architecture design, solution proposals, pricing input, and alignment with commercial strategy.
• Build strong relationships with senior technical stakeholders (CIOs, CTOs, IT leadership).
• Design secure, scalable GPU-based architectures for AI/ML and HPC workloads.
• Develop high-level architecture blueprints using platforms such as Kubernetes, Red Hat, Azure ML, and NVIDIA technologies.
• Ensure solution designs meet performance, security, compliance, and interoperability requirements.
• Collaborate with technology partners to enhance solution offerings and market positioning.
• Lead the creation of technical documents including SoWs, RFx responses, and pricing models.
• Conduct executive workshops, PoCs, and enablement sessions to support AI solution adoption.
• Develop sector-specific use cases and reference architectures.
• Promote DevSecOps, containerization, and platform automation practices.

Minimum Experience & Skills

• 10+ years in solution architecture, technical consulting, or infrastructure engineering.
• 3+ years in AI/ML delivery or AI infrastructure design.
• Strong background in hybrid cloud, data center infrastructure, and GPU-based computing.
• Deep knowledge of enterprise IT, networking, security, and compliance frameworks.
• Strong business acumen and ability to present complex AI concepts to non-technical stakeholders.
• Proficiency with AI/ML workflows and APIs (e.g., Azure AI, OpenAI, Hugging Face).
• Experience in regulated industries is an advantage.

Analytical & Soft Skills

• Ability to translate customer challenges into AI use cases and viable technical solutions.
• Strong communication and stakeholder-management skills.
• Ability to collaborate effectively across cross-functional teams.

Education

• Bachelor’s degree in IT, Computer Science, or Engineering (required).

Preferred Certifications

• Enterprise Architecture certifications
• Solution Architect certifications
• AI/ML certifications (TensorFlow, Azure AI, NVIDIA DLI, etc.)

Technical Competencies

CompetencyLevel

Solution Design

Expert

AI Use Cases

Expert

Cloud Computing

Advanced

Compute, Network, Storage

Advanced

Leadership & Behavioral Competencies

Intermediate: Building Customer Value, Collaboration & Delivery, Strategy, Change Management, Networking & Influence

Basic: Leading Teams