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AI Engineer I/II/III

Remote

At EQT, you won't just do a job, you'll help shape our future. Through Transparent Leadership, you'll work alongside leaders who value collaboration and ensure every voice is heard. Through Connected Impact, you'll see how your work influences critical business decisions and drives value across our operations. Through Supported Growth, you'll have opportunities to expand your skills through cross-functional collaboration, development opportunities, and career advancement.

Join our Qrew! 

EQT is building a fleet of AI agents that work alongside our people, and we need an AI Engineer to help it grow. You'll join an AI team that builds the shared tools agents rely on, configures and deploys the agents themselves, and keeps the whole fleet healthy once it's live.

Our agents already run in production on Microsoft Foundry, posting into Salesforce and the enterprise systems our people use every day. The next step is scale: many more agents, built faster, with business users helping tune them.

As an AI Engineer, you build and maintain the capabilities our agents run on, and you monitor and optimize the agent fleet once it's in production. You set up the configuration for each prompt agent and customize its tools. Then you hand off to AI Specialists and domain experts, who test against real cases and tune the prompts until the agent is right.

When reasoning alone can't do the job reliably, you build a pro-code hosted agent or specialized tooling. That's the exception, not the plan.

 

The AI Engineer I/II/III responsibilities include but are not limited to:

  • Build and maintain shared agent tools and capabilities.
  • Configure Foundry prompt agents: instructions, model selection, tool assignments, permissions, and guardrails, ready for others to test and tune.
  • Customize and extend tools when an agent needs something the shared set doesn't yet cover.
  • Partner with AI Specialists and domain experts as they test against real cases, and coach them on prompt design and evaluation.
  • Deploy agents and monitor the fleet through the Foundry control plane: evaluations, monitoring and alerts, audit trail, and cost.
  • Optimize agents in production, and recognize when a deployment is drifting or needs tighter guardrails, better data, or a narrower scope.
  • Build pro-code hosted agents or specialized tooling when review shows a prompt agent can't do the job reliably.
  • Ensure agents adhere to our security and identity standards.
  • Help shape the Agent Factory standards and share what you learn, so the next agent is faster to build than the last.
  • Stay current with models, agent frameworks, and Foundry features, and bring forward ideas that move more work from code to reasoning.

 

Required Experience and Skills:

  • Bachelor's degree in a technical discipline (computer science, engineering, information systems, or similar), or an equivalent combination of education and experience.
  • 3+ years of professional experience in software engineering, data engineering, or AI/ML roles.
  • Hands-on experience building LLM-based agents or applications: prompt design, tool calling, retrieval, and evaluating outputs against real cases.
  • Solid software engineering fundamentals in Python, including git, code review, testing, and working with APIs.
  • Working experience with Microsoft Azure or a similar cloud platform, including identity, permissions, and secrets management.
  • Comfort working across enterprise systems and data, including SQL and integrating with platforms like Salesforce and Databricks.
  • Judgment about when code is the right answer versus when a well-designed prompt and the right tools are simpler and just as successful.
  • Clear communicator who can explain technical tradeoffs to business partners and coach non-engineers as they test and tune agents.

 

Preferred Experience and Skills:

  • Experience with Microsoft Foundry (Azure AI Foundry): prompt agents, hosted agents, tools, evaluations, and the control plane.
  • Exposure to agent frameworks and protocols such as Model Context Protocol (MCP), LangGraph, Semantic Kernel, or similar.
  • Working knowledge of Salesforce (configuration, security model, Flow) and the Databricks ecosystem (Unity Catalog, Databricks SQL).
  • Experience operating AI in production: monitoring, evaluation harnesses, cost tracking, and responsible AI practices such as PII handling, guardrails, and human-in-the-loop review.

 

Remote work is being considered for this role excluding the following states:  California, Connecticut, Delaware, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, and Tennessee unless willing to relocate.


Selected incumbent will be placed into the position that best suits their abilities and experience level.

EQT Corporation and its subsidiaries is an Equal Opportunity Employer -- Disabilities/Veterans.

 

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