Solutions Architect - AI Platform

As Solution Architect you own the technical design of the enterprise AI platform. You turn our target architecture into a buildable plan, make the key design decisions, and make sure every workflow team builds on the same shared foundation rather than reinventing it.

Duties

• Own the end-to-end architecture of the enterprise AI platform on Azure: AI gateway and model routing, generative AI and machine learning services, agent orchestration, memory and retrieval, data integration, guardrails, security, evaluation and observability.
• Define the minimum platform needed to start building the first workflows, then lay out the roadmap for later capabilities such as a semantic layer, centralized orchestration and an evaluation framework.
• Set the standards every workflow team follows: how AI solutions and agents are onboarded, how autonomy and human review are set per workflow, how tenancy and data isolation work, and how models and agents are evaluated.
• Design integrations with our core fund administration systems, Snowflake data platform, MCP servers, document stores and third-party APIs.
• Partner with security, compliance and risk teams so the platform meets our regulatory, data-protection and audit requirements from day one.
• Review designs from the AI Development pods and make build-versus-buy and vendor recommendations.
• Work alongside external partners during the initial build and make sure knowledge transfers to the Ultimus team.

Requirements

• 8+ years in software or cloud architecture, including 2+ years designing production AI, ML or LLM-based systems. •
• Deep hands-on experience with Microsoft Azure (AKS, API Management, networking, identity and Key Vault). •
• Working knowledge of modern AI application patterns: machine learning operations, retrieval-augmented generation, agent orchestration, tool calling, prompt and context management, and evaluation. •
• Experience designing secure, multi-tenant platforms that handle sensitive financial or personal data. •
• Strong data architecture background, including data warehouses and integration patterns. • Ability to explain technical trade-offs clearly to engineers, operations leaders and executives. Nice to have • E
• xperience with agent frameworks and protocols (for example, Model Context Protocol, LangGraph, Semantic Kernel or similar). •
• Background in financial services, fund administration or asset management. •
• Experience with Snowflake and knowledge graph or semantic layer design. •
• Azure Solutions Architect Expert or similar certification.

Our technology- Microsoft Azure (AKS, API Management, Service Bus, Key Vault, Entra ID, Azure AI services), Snowflake, MCP servers, Python and .NET, Azure DevOps, and leading large language models.