About The Position

We are seeking a highly motivated Application Engineer, Agentic Workflows to help build and deliver the next generation of AI Physics capabilities at Rescale! You will work directly with platform and AI teams to design and ship agent-based capabilities that operate on real engineering tools and data. You will also work closely with customers to apply these agents to real workflows, ensuring what gets built is reliable, repeatable, and productizable. The role is customer-facing, but product-first. Work done in customer environments must translate into reusable product capabilities rather than one-off solutions. This role is ideal for engineers who enjoy building real systems, integrating with complex engineering software, and turning early agent prototypes into durable platform capabilities.

Requirements

  • Strong software engineering fundamentals, with heavy emphasis on Python
  • Hands-on experience building automation around engineering or technical software
  • Familiarity with CAE workflows, simulation data, and solver-driven processes
  • Experience building or deploying agent-based or LLM-driven systems
  • Experience orchestrating tools, scripts, or workflows across multiple systems
  • Ability to design deterministic, reliable automation around complex tools
  • Experience turning internal automation into reusable, product-grade components
  • Comfortable debugging across tool execution, data handling, and orchestration layers

Responsibilities

  • Build and ship agent-driven automation across engineering and CAE workflows
  • Design and implement agents that interact with engineering tools, simulation data, and workflows
  • Encode engineering workflows as structured, agent-executable steps with clear inputs, outputs, and guardrails
  • Integrate agents into end-to-end pipelines as reusable capabilities rather than one-off scripts
  • Harden early agent use cases into deterministic, production-ready systems
  • Debug and resolve issues across agent logic, tool execution, data handling, and orchestration
  • Work directly with customer engineers to understand real workflows and technical constraints
  • Close gaps between real workflows and platform capabilities, feeding concrete learnings back into product direction
  • Operate as a builder first, with the ability to be forward-deployed on critical engagements when needed
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