Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

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 Sr. AI Solution Engineer, you will lead the AI SWAT team's embedded engagements with business units, owning the path from opportunity to production artificial intelligence (AI) agent and the business results that follow. Rotating across Sales, Accounting/Finance, Marketing, Legal/HR, and Supply Chain/Operations, set the technical approach for each engagement, design and build the most complex solutions using Microsoft Copilot Studio, Microsoft Foundry, OpenAI and Claude models, Agentforce, and Microsoft Fabric data, and decide when to configure, build, or buy. Mentor and review the work of the AI Engineer, partner with the AI Architect and AI Data Engineer on reusable patterns, and report value realized to business leaders and the AI Steering Committee.

The Impact You'll Make:

Engagement Leadership & Use-Case Portfolio — Lead embedded engagements with business-unit leaders; run discovery, ride-alongs, process mapping, and value sizing; own a prioritized portfolio of AI use cases per business unit with baselines, target key performance indicators (KPIs), and business cases.

Solution Design & Technical Approach — Set the technical approach for each solution: choose the platform (Microsoft Copilot / Copilot Studio, Microsoft Foundry / Azure OpenAI, Salesforce Agentforce, SAP Joule) and model (e.g., OpenAI GPT-5.6, Claude Sonnet 5.5 or Opus 5.5), design multi-step and multi-agent workflows with human-in-the-loop controls, and make configure-build-buy recommendations within the AI Architect's standards.

Build Complex Production Agents — Personally build and ship the most complex agents and automations, including custom code with OpenAI / Azure OpenAI and Claude tool calling, agent frameworks, Model Context Protocol (MCP) tools across Salesforce and SAP, retrieval over Microsoft Fabric and SharePoint content, and Continuous Integration / Continuous Delivery (CI/CD); use Cursor or Claude Code to accelerate delivery.

Evaluation Strategy & Production Readiness — Define evaluation strategy and acceptance criteria (accuracy, groundedness, safety, cost per task); approve production readiness; lead Responsible AI (RAI), security, privacy, and legal reviews for team solutions.

Mentorship & Quality Review — Mentor the AI Engineer; review prompts, code, flows, and evaluation results; set team delivery standards, estimates, and engagement playbooks.

Executive Communication & Value Realization — Present solution designs, trade-offs, and results to directors and vice presidents; track and report value realized (hours returned, cycle time, quality, adoption, cost) in Power BI to business leaders and the AI Steering Committee.

Adoption & Change Leadership — Lead adoption and workflow redesign with process owners; plan rollout, training, and support handoff so solutions are sustained in steady-state operations.

Pattern Contribution & Platform Feedback — Turn proven solutions into reusable agent templates, prompt libraries, MCP tools, and workflow templates; bring platform and data requirements to the AI Architect and AI Data Engineer and help shape team standards.

Who You Are:

Prefer a Bachelor's Degree in the field of Computer Science, Information Systems, Artificial Intelligence, or related; Master's degree (MS) in a related field preferred.

3-5 years of experience in building AI-enabled apps, enterprise automations, or business-facing software in solutions engineering or development roles

1-3 years of experience in leading delivery of production generative AI solutions (copilots, agents, LLM-powered workflows) end to end, including stakeholder ownership, evaluation, and responsible AI review

Computer Skills Desired: AI platforms: Microsoft Copilot / Graph / Copilot Studio, Microsoft Foundry / Azure OpenAI, Salesforce Agentforce; familiarity with SAP Joule

Additional Knowledge or Skills to be Successful in this role: Trusted advisor to business leaders who can lead an engagement independently; strong facilitation, storytelling, and executive presence; product mindset focused on adoption and measurable outcomes; coaches the AI Engineer and raises team quality.

Models: OpenAI GPT-5.6 / GPT-6, Anthropic Claude Opus 5.5 / Sonnet 5.5 / Haiku 5.5, Google Gemini 3.1 Pro; OpenAI and Claude tool calling, Model Context Protocol (MCP), RAG, prompt and context engineering

Agent frameworks: LangChain, Semantic Kernel, or equivalent

Integration / automation: Power Platform / Power Automate, MuleSoft / Workato, Salesforce Flow; Zapier for quick pilots

Data: Microsoft Fabric, Power BI, SQL

Languages: TypeScript/JavaScript and Python

DevOps / collaboration: Git, CI/CD, Cursor or Claude Code, work tracking (Azure DevOps / Jira), documentation (Confluence / SharePoint)

Telemetry: Application Insights / Log Analytics or equivalent; Copilot Studio and Foundry evaluations

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

Salesforce Platform Developer I or Agentforce Specialist (for Sales-heavy rotations)

Workato / MuleSoft integration certification; Responsible AI / governance training aligned to internal standards

Monster Energy provides competitive total compensation. The estimated annual salary range for this position is listed below. Actual compensation may vary based on skills, qualifications, experience, and work location.

Pay Range $131,250 — $175,000 USD

Monster Energy uses AI-powered tools, including Greenhouse’s Talent Matching feature, to help evaluate applications for this role. To learn more see Monster’s privacy policy here Privacy Policy or contact Monster at privacy@monsterenergy.com.

For United States applicants: Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor. Read our privacy policy here: Privacy Policy