Key skills
AIMLClaudeAgenticAWSAzureIAMBedrockLeadershipChange ManagementCommunicationPresentation Skills
About this role
AI Architect - DC/VA - Onsite
Required Skills & Experience
- 8–12 years of experience in AI/ML architecture, orchestration, or ITSM automation.
- Prior work in regulated enterprise environments with compliance-heavy workflows.
- Exposure to AI governance frameworks and enterprise adoption strategies.
- Agentic Platforms: Proven expertise with Workato, AWS Bedrock Agents, Claude Agentic Orchestration, Digitalnet.ai, Serval, Atomic Work, Harmony.ai, and Leena.ai.
- Enterprise Architecture: Strong background in hybrid cloud (Azure + AWS), API integration, and orchestration frameworks.
- Governance & Compliance: Experience with AI governance platforms (Credo.AI or equivalent), IAM/RBAC, audit logging, and regulatory alignment.
- Data Architecture: Skilled in data wrangling, feature engineering, and pipeline design for AI/ML workflows.
- ITSM Knowledge: Deep understanding of incident management, service requests, and change management automation.
- Leadership: Ability to lead cross-functional teams, mentor developers, and engage with vendors and stakeholders.
- Soft Skills: Strong communication, documentation, and presentation skills for executive and technical audiences.
Key Responsibilities
- Architecture & Strategy
- Define enterprise architecture for agentic AI orchestration and ITSM automation.
- Design integration blueprints across hybrid cloud environments (Azure + AWS).
- Establish scalability, security, and compliance frameworks for agentic workflows.
- Platform Evaluation & Selection
- Lead comparative assessments of Workato, AWS, Claude, Digitalnet.ai, Serval, Atomic Work, Harmony.ai, and Leena.ai.
- Document pros/cons, risks, and vendor maturity for leadership decision-making.
- Governance & Compliance
- Implement governance controls using Credo.AI (policy enforcement, explainability, audit readiness).
- Ensure IAM/RBAC alignment across orchestration and ITSM platforms.
- Data Architecture
- Oversee data wrangling, preparation, and integration
- Define data pipelines for anomaly detection, compliance validation, and ITSM automation.
- Leadership
- Guide AI Developers in building and testing sandbox environments.
- Validate vendor claims against real-world performance and enterprise requirements.
- Stakeholder Engagement
- Liaise with business units, ITSM teams, and compliance officers to align technical solutions with operational needs.
- Present architecture diagrams, phased roadmaps, and executive-ready reports.