AI Engineer

About Monster Energy:

Forget about blending in. That's not our style. We're the risk takers, the trailblazers, the gamechangers. We're not perfect and we don't pretend to be. We're raw, unfiltered, and a bit unconventional. Our drive is just like our athletes, unrivaled. The power is in your hands to define what success looks like and where you want to take your career. It's not just about what we do, but about who we become along the way. We are much more than a brand here. We are a way of life, a mindset. Join us.

A Day in the Life:

In the position of AI Engineer, you will build, test, and run production artificial intelligence (AI) agents, Model Context Protocol (MCP) tools, and integrations on Monster's AI platform, working under the technical direction of the AI Architect and alongside the Sr. AI Solution Engineer. Write pro-code solutions in Python and TypeScript using OpenAI and Claude models, Microsoft Foundry, and Copilot Studio; build automated tests and evaluations into every release; and keep live agents reliable, secure, and cost-efficient. Turn designs into working software quickly and add reusable components that make each new solution faster to deliver.

The Impact You'll Make:

• Build Production Agents — Build and ship agents and automated workflows in Python and TypeScript using OpenAI / Azure OpenAI and Claude models, Microsoft Foundry, and Copilot Studio, following the AI Architect's reference patterns and security standards.
• MCP Servers & Tools — Build and maintain MCP servers and tools that connect agents to Salesforce, SAP, Workday, SharePoint, and Microsoft Fabric data; publish them to the shared tool registry with schemas, versioning, and documentation.
• Testing, Evaluation & CI/CD — Write automated tests and evaluation suites (accuracy, groundedness, safety, tool-call correctness) and run them in Continuous Integration / Continuous Delivery (CI/CD) pipelines so every release is gated on quality.
• Integrations & Orchestration — Develop REST, GraphQL, webhook, and event-based integrations, and orchestration with Power Automate, Salesforce Flow, Workato, or MuleSoft, with proper error handling and retries.
• Observability & Production Support — Instrument agents with logging, tracing, and telemetry (e.g., Application Insights / Log Analytics); monitor reliability, latency, and token cost; troubleshoot and resolve production issues.
• Security & Responsible AI — Apply least-privilege access, secrets management, and prompt-injection defenses; follow Responsible AI (RAI), privacy, and security standards; document data use, risks, and mitigations.
• Reusable Components — Package proven code into reusable agent templates, prompt libraries, connectors, and MCP tools that the team and business units can reuse.
• Collaboration & Documentation — Work with the Sr. AI Solution Engineer on business requirements and the AI Data Engineer on data needs; write runbooks and technical documentation; use AI coding agents (e.g., Cursor, Claude Code) daily to accelerate delivery.

Who You Are:

• Prefer a Bachelor's Degree in the field of -- Computer Science, Software Engineering, Artificial Intelligence, or related; Master's degree (MS) in a related field preferred.
• 3-5 years of experience in software engineering, including building production applications or integrations in Python or TypeScript
• 1-3 years of experience in building generative AI applications or agents in production (LLM APIs, tool calling, RAG, MCP)
• Computer Skills Desired: Languages: Python and TypeScript/JavaScript (strong); SQL; C# a plus
• Models & APIs: OpenAI GPT-5.6 / GPT-6 and Anthropic Claude Sonnet 5.5 / Haiku 5.5; tool calling, structured outputs, retrieval-augmented generation (RAG), Model Context Protocol (MCP)
• AI platforms: Microsoft Foundry / Azure OpenAI, Copilot Studio; LangChain or Semantic Kernel
• Integration: REST, GraphQL, webhooks, event systems; Power Automate / Power Platform, Salesforce Flow, Workato or MuleSoft
• Data: Microsoft Fabric / OneLake, Azure AI Search, SQL; Power BI basics
• DevOps: Git, CI/CD (Azure DevOps or GitHub Actions), automated testing and evaluation frameworks, containers
• Observability: Application Insights / Log Analytics or equivalent
• AI-assisted development: Cursor, Claude Code, or GitHub Copilot used daily
• Preferred Certifications: Microsoft AI-103: Developing AI Apps and Agents on Azure (replaces the retired AI-102 / Azure AI Engineer Associate)
• Microsoft Power Platform Developer Associate (desirable)
• Databricks Certified Generative AI Engineer Associate (desirable)
• Responsible AI / governance training aligned to internal standards
• Additional Knowledge or Skills to be Successful in this role: Strong engineering fundamentals and code quality; takes designs from the AI Architect to production quickly; comfortable owning live systems; learns new models and tools fast; writes clear technical documentation.