Agentic Advisor RoleRole Overview
We are seeking an experienced Agentic AI Advisor to help organizations define, design, and implement enterprise-grade Agentic AI solutions. The ideal candidate will have expertise in Large Language Models (LLMs), AI agents, orchestration frameworks, enterprise architecture, cloud platforms, and responsible AI practices.
The role requires deep expertise in enterprise-scale Databricks architecture, multi-cloud AI ecosystems, security frameworks, governance models, observability, platform engineering, and operational excellence for large-scale AI/LLM environments.
The architect will work closely with Cloud Engineering, Platform Engineering, Security, DevOps, Infrastructure, FinOps, and Operations teams to design and operationalize a centralized, secure, scalable, observable, and governed enterprise AI platform across cloud and on-prem ecosystems.
Key Responsibilities
Lead architecture and implementation of enterprise AI platforms leveraging Databricks AI Gateway as the centralized control plane for: - LLM access management
- Agent orchestration
- Policy enforcement
- Model governance
- Telemetry collection
- Rate limiting
- Prompt protection
- Observability
Design and operationalize enterprise AI platform architectures across multi-cloud and hybrid/on-prem environments.Collaborate with Cloud, Security, Infrastructure, DevOps, and Platform Engineering teams to establish scalable and secure AI platform patterns.Design enterprise-grade telemetry, monitoring, and observability frameworks using OpenTelemetry (OTEL), Databricks MLflow, system tables, and Unity Catalog.Partner with Security and IAM teams to implement: - RBAC
- Least privilege access
- Managed identities
- Federated identities
- Enterprise IAM integration
Define governance, compliance, auditability, and operational controls for enterprise AI workloads.Design integrations with: - Azure AI Foundry
- AWS Bedrock
- Oracle AI Services
- ServiceNow AI Agents
- NVIDIA AI infrastructure / Run.AI
Collaborate with SIEM and Security Operations teams for enterprise monitoring integrations with Microsoft Sentinel and related security platforms.Work with API management teams to operationalize AI access through: - Azure API Management (APIM)
- AWS API Gateway
Partner with FinOps and Operations teams to establish AI cost governance and optimization frameworks for:- LLM usage
- API consumption
- Infrastructure utilization
- Agent execution costs
Contribute to reusable enterprise architecture standards, governance models, security controls, and operational best practices.Support platform reliability, automation, CI/CD enablement, and operational excellence initiatives with DevOps and SRE teams.Required Skills & Experience
- 15+ years of experience in enterprise platform architecture, cloud engineering, or data/AI platform architecture
- Strong expertise in Databricks platform architecture and ecosystem
- Hands-on experience with:
- Databricks AI Gateway
- Unity Catalog
- MLflow
- Lakehouse architecture
- Strong knowledge of:
- Multi-cloud architectures (Azure/AWS)
- Enterprise security and IAM
- Observability frameworks
- OpenTelemetry (OTEL)
- API management platforms
- Experience designing governance and operational frameworks for enterprise AI/LLM platforms
- Experience collaborating across Security, Infrastructure, Cloud, DevOps, and Operations teams
- Strong understanding of enterprise AI operationalization and governance patterns
Preferred Skills
- Experience with enterprise GenAI and agentic AI platforms
- Exposure to NVIDIA AI infrastructure and Run.AI
- Experience with Microsoft Sentinel / SIEM integrations
- Familiarity with FinOps practices for AI platforms
- Knowledge of CI/CD and SRE practices for AI platforms
- Strong stakeholder management and leadership skills
