Technical Solution Architect

We are seeking a highly motivated and hands-on Technical Solution Architect (with 15+ years of experience) to help design and implement a unified enterprise AI and agentic workflow platform centred around Databricks AI Gateway. The role requires strong architectural knowledge across enterprise AI ecosystems, observability, governance, cloud platforms, security frameworks, and operationalisation of large-scale AI/LLM environments.

The ideal candidate should possess a deep understanding of Databricks, AI/LLM platforms, multi-cloud architectures, observability frameworks, identity and access management, API gateways, and enterprise governance models.

The architect will collaborate extensively with Cloud Engineering, DevOps, Platform Engineering, Security, Infrastructure, and Operations teams to deliver a centralised, secure, observable, scalable, and governed enterprise AI platform across cloud and on-prem environments.

Responsibilities:

• Possess strong architectural and implementation knowledge of enterprise AI solutions leveraging Databricks AI Gateway as a centralised control plane for LLM access, agent orchestration, model governance, policy enforcement, telemetry collection, rate limiting, prompt protection, and observability.
• Work in close collaboration with Cloud, DevOps, Security, Infrastructure, and Platform Engineering teams to design and operationalise unified agentic AI workflow platforms across cloud and on-premises ecosystems.
• Demonstrate expertise in integrating enterprise AI services and platforms, including AWS Bedrock, Azure AI Foundry, ServiceNow AI Agents, Oracle AI Services, and NVIDIA on-prem AI infrastructure using Run. AI, MCP servers, and direct agent integrations.
• Partner with observability and platform teams to design enterprise-grade telemetry and observability pipelines using Open Telemetry (OTEL).
• Collaborate with security and governance teams to ensure telemetry, traces, logs, prompts, model outputs, alerts, and usage metrics from external systems are consolidated into the following: Databricks MLflow, Databricks system tables, and Unity Catalogue-governed environments.
• Work alongside Security Operations and SIEM teams to enable downstream integrations with Azure SIEM / Microsoft Sentinel for enterprise monitoring, governance, and security operations.
• Possess a strong understanding of secure AI access patterns and collaborate with security and IAM teams to implement the following: Managed identities, federated identities, IAM, RBAC, and least privilege access models.
• Partner with business, operations, and platform teams to build operational and executive dashboards using Power BI and Databricks Dashboards.
• Collaborate with Cloud and FinOps teams to monitor and optimise LLM usage costs, agent execution costs, infrastructure utilisation, and API consumption.
• Work with enterprise API management and DevOps teams to design and operationalise integrations using Azure API Management (APIM) and AWS API Gateway.
• Support automation, CI/CD integration, platform reliability, governance enforcement, and operational excellence initiatives in coordination with DevOps and SRE teams.
• Contribute to enterprise AI platform standards, reusable architecture patterns, security controls, governance frameworks, and operational best practices.

Skills

AI, Databricks, LLM, architect, architecture