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Applications Engineers, Agentic Workflows

AI Engineer Full-time Permanent United States

Job details

$156K – $180K • Offers Equity Salary
United States Eligibility
Not specified Experience
Full-time Employment

About this role

Role overview Build and deliver agent-driven automation for engineering and computer-aided engineering workflows. This customer-facing role combines hands-on development with product work: learn how engineers use complex tools and simulation data, then turn successful deployments into reliable, reusable platform capabilities.

Responsibilities - Design and implement agents that interact with engineering applications, simulation data, and technical workflows. - Represent engineering processes as structured steps with defined inputs, outputs, and safeguards. - Connect agents to end-to-end pipelines and develop reusable capabilities instead of isolated scripts. - Mature early use cases into dependable, production-ready automation. - Diagnose issues across agent behavior, tool execution, data handling, and workflow coordination. - Work directly with customer engineers to understand constraints, identify gaps, and feed practical findings into product development.

Requirements - Strong software engineering fundamentals, especially in Python. - Hands-on experience automating engineering or other technical software. - Experience building or deploying agent-based or LLM-driven systems. - Ability to coordinate scripts, tools, or workflows across multiple systems. - Skill in designing reliable, predictable automation for complex tools and debugging across system layers. - Experience turning internal automation into reusable, product-quality components.

Nice to have Familiarity with computer-aided engineering workflows, simulation data, and solver-driven processes.

Benefits and work setup The position includes direct customer work during deployments and early workflow rollouts, with occasional travel to customer sites for technical sessions or key milestones.

Skills detected in the listing

PythonLLM
Detected Nov 3, 2026
Last verified Nov 12, 2026

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