Expertshub.ai
Senior Enterprise AI Architect
Lead architectural design and strategic delivery of enterprise AI solutions (LLMs, RAG, multi-agent systems) across AWS, Azure, and GCP, establishing governance standards and driving program-scale execution in a remote setting.
- Compensation
- Not disclosed
- Location
- Worldwide
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Architecture
- Posted
Skills
Must have
- Docker & Kubernetes
- AI Architecture design
- AI Governance and Policy Development
- AI/ML architecture
- AWS
- Azure
- C-Suite Influence
- Corporate Vision Setting
- Executive Level Decision Making
- GCP AI ecosystems
- Large Language Models (LLMs)
- Long-Term Organizational Impact
- Model Context Protocol
- Multi-Agent Systems
- P&L Management
- RAG
- Strategic Leadership
- 12 to 15 years of experience
Nice to have
- Industry Disruption Leadership
- Global Policy Influence
- Corporate Social Responsibility
- Legacy Building
Full description
Title: Senior Enterprise AI Architect
Industry: IT | Work Mode: Remote
Role Summary
As a Senior Enterprise AI Architect, you will lead the strategic delivery and architectural design for AI-driven solutions within the Information Technology industry. This role involves transforming business objectives into actionable programs that yield measurable outcomes. You will establish governance standards to ensure predictable execution, aligning with the constraints of remote work.
Responsibilities
- Design and implement comprehensive delivery strategies that encompass program scale and architecture, ensuring alignment with business goals and industry standards.
- Develop realistic project plans and estimates while maintaining transparency on milestones and overall project status.
- Sponsor proof-of-concept initiatives where necessary, establishing clear criteria for project approval and progression.
- Coordinate responses to incidents and issues, facilitating post-incident reviews to incorporate lessons learned into future initiatives.
- Maintain rigorous change control and documentation standards across all projects to ensure consistency and quality.
Ways of Working
- Establish a standardized definition of project completion, testing protocols, and review quality across multiple teams to ensure alignment and efficiency.
- Keep project budgets, efforts, and throughput visible within internal processes to maintain accountability and transparency.
- Enforce asynchronous communication rituals to foster clarity in ownership and decision-making in a remote work environment.
Collaboration & Communication
- Collaborate closely with senior leadership to coach team members, set clear expectations, provide feedback, and identify succession planning opportunities.
- Engage with hiring managers to signal the need for specific skills aligned with project requirements and educational qualifications.
Growth Signals
- Monitor health metrics such as on-time delivery across releases, stable throughput, and lead time to gauge project success.
- Track trends in critical defects and production incidents to drive continuous improvement and enhance service quality.
Must-Haves
- Docker & Kubernetes, AI Architecture design, AI Governance and Policy Development, AI/ML architecture, AWS, Azure, C-Suite Influence, Corporate Vision Setting, Docker, Executive Level Decision Making, GCP AI ecosystems, Kubernetes, Large Language Models (LLMs), Long-Term Organizational Impact, Model Context Protocol, Multi-Agent Systems, P&L Management, RAG, Strategic Leadership