AI Architect

Monster Energy•Corona, CA

6h•$150,000 - $200,000

About The Position

The AI Architect will design and own the technical integration layer connecting Monster Energy’s AI platforms—including Microsoft Copilot and Copilot Studio, Microsoft Foundry and Azure OpenAI, Salesforce Agentforce, SAP Joule, and Workday—to company applications and the Microsoft Fabric data estate. The role defines reference architecture, integration standards, and security patterns governing how AI agents access enterprise data and tools through MCP, APIs, and events; collaborate with other agents and people; and use models selected for each use case. The AI Architect builds core connectors and reference implementations for reuse by the Sr. AI Solution Engineer and AI Engineer, helping turn individual AI projects into a governed, scalable enterprise platform. The position also provides technical leadership and design review for AI engineering colleagues, establishes reusable golden-path templates, evaluates vendor AI capabilities, and documents architecture and governance evidence. The role partners with Information Security and supports AI governance, audit, and regulatory requirements.

Requirements

5+ years of experience in enterprise integration, software, or solution architecture, including APIs, event-driven systems, or integration platforms.
1–3 years of experience designing and delivering production AI agent or LLM solutions, including MCP-style connectors, tool calling, and at least one enterprise AI agent framework.
Deep working knowledge of current AI architecture patterns and when to use them.
Ability to turn business processes into secure, reusable agent architecture and establish standards adopted by other teams.
Ability to communicate trade-offs clearly to executives and engineers.
Hands-on technical leadership and ability to mentor AI engineering colleagues.
Knowledge of AI architecture patterns including RAG and agentic RAG, tool/function calling, MCP client-server design, multi-agent orchestration, human-in-the-loop, guardrails, AI gateways and model routing, caching, structured outputs, agent memory, and evaluation-driven development.
Knowledge of models including OpenAI GPT, Anthropic Claude, Google Gemini, and open-weight models, plus awareness of GPU/CUDA inference trade-offs.
Experience or skills with AI tools and platforms such as Microsoft Copilot Studio, Microsoft Foundry/Azure OpenAI, OpenAI function calling, Claude tool use and MCP, Joule skills, Agentforce prompts, and LangChain or Semantic Kernel.
Programming skills in TypeScript/JavaScript, Python, or C#; React familiarity.
Knowledge of REST, GraphQL, webhooks, event systems, and integration platforms such as MuleSoft, Workato, Power Platform/Power Automate, Salesforce Flow/Agentforce, and SAP BTP.
Knowledge of Microsoft Fabric/OneLake, Azure SQL, and Power BI.
Knowledge of Git, CI/CD, environment configuration, Azure DevOps, Microsoft Entra ID, and Application Insights/Log Analytics.
Experience or knowledge of Azure, Salesforce, SAP BTP, or equivalent cloud platforms.
Daily use of AI-assisted development tools such as Cursor, Claude Code, or GitHub Copilot.

Nice To Haves

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Artificial Intelligence, or a related field is preferred.
Microsoft AI-103: Developing AI Apps and Agents on Azure certification.
Microsoft Certified: Agentic AI Business Solutions Architect (AB-100) or Azure Solutions Architect Expert (AZ-305) certification.
Salesforce Platform Developer I or Integration Architect certification.
Microsoft Power Platform Developer Associate certification.
Workday Integration certification, if applicable.
SAP BTP/Joule configuration training.

Responsibilities

Define and maintain enterprise AI reference architecture across Microsoft, Salesforce, SAP, and Workday ecosystems.
Select and standardize AI architecture patterns, publish standards and decision records, and lead architecture reviews for proposed AI use cases.
Design, build, and operate an MCP gateway and governed registry of MCP servers and tools that expose enterprise systems and Microsoft Fabric data to AI agents.
Manage tool approvals, versioning, schemas, and descriptions so tools can be reused across compatible AI platforms and clients.
Implement least-privilege agent identities, delegated authorization, secrets management, and API controls.
Design defenses against prompt injection, tool poisoning, and data exfiltration; partner with Information Security on threat models and AI red-team testing.
Set model selection and routing guidance based on cost, quality, latency, and data sensitivity.
Architect agent handoffs between agents and people using agent frameworks and emerging agent-to-agent standards.
Build and maintain secure integrations between AI agents and CRM, ERP, HRIS, finance, and collaboration systems.
Instrument agents and integrations with logging and telemetry; establish automated evaluation and regression tests for quality, safety, and tool-call accuracy.
Monitor latency, reliability, model use, and token consumption to manage operating costs.
Serve as technical lead and design reviewer for the Sr. AI Solution Engineer, AI Engineer, and AI Data Engineer; mentor these colleagues and publish reusable templates.
Evaluate vendor AI capabilities and recommend build-versus-buy decisions.
Document integration contracts, the MCP tool catalog, prompts, runbooks, and architecture decisions; provide evidence for AI governance, audit, and regulatory requirements.