Field Solutions Engineer (Copy)

Summary

nTop builds next-generation engineering solutions that help innovative companies develop, test, and manufacture better products. The Field Solutions Engineer will embed with strategic Aerospace & Defense customers to build nTop workflows, design automation, proofs of concept, and AI-enabled engineering integrations, while supporting pre-sale demonstrations and post-sale workflow consultations.

Responsibilities

• Own technical project components within strategic customer and partner engagements, taking direction from the engagement lead
• Deliver to a clear definition of done, and surface risks and blockers early
• Build nTop workflows, design automation, and proofs of concept against real customer data, including headless and batch execution for DOE, parameter sweeps, and surrogate-model training data
• Write Python tooling and integrations that connect nTop to customer toolchains such as CAD, FEA/CFD, MDO frameworks, and agentic frameworks (e.g., MCP-style tool interfaces)
• Help shape the architecture of emerging workflows: how nTop, simulation, data, compute, and AI agents connect end to end, and what it takes to move a proof of concept into production
• Use AI-assisted development and agentic tools as part of your normal workflow, and feed what works back to the team and Product
• Support the technical sales process through discovery, demonstration, and proof of concept development
• Deliver tailored product demos aligned with customer use cases, including AI-embedded and agentic workflow demos
• Lead technical sessions such as solution reviews and scoping calls to help customers expand usage and realize value
• Resolve workflow consultation requests across design automation and workflow development

Skills

• A Bachelor's and/or Master's degree in Mechanical, Aerospace, Computational Engineering, or a related engineering discipline, plus 3+ years of industry experience (highly relevant doctoral degrees can be substituted for three years)
• Working knowledge of the aerospace design and analysis toolchain, including at least one of: parametric CAD (CATIA, Siemens NX, SolidWorks, Onshape); FEA (Nastran, Abaqus, Ansys, LS-DYNA); CFD (Fluent/CFX, Star-CCM+, OpenFOAM); conceptual design and MDO tools (OpenVSP, OpenMDAO, ModelCenter, HEEDS, Isight); or PLM (Teamcenter, 3DEXPERIENCE, Windchill)
• Experience scripting in Python, including tools or integrations used by other engineers
• Familiarity with the scientific Python stack (NumPy, SciPy, pandas), LLM APIs, agent frameworks, or tool-calling protocols (e.g., MCP), or at least one ML framework
• Demonstrated ability to learn new technical software quickly
• Systems thinking: able to map how geometry, simulation, data, and AI components fit together across a toolchain and reason about where automation adds the most value
• Excellent communication and presentation skills, with the ability to explain complex topics to technical and non-technical audiences, including large groups and senior-level stakeholders
• Demonstrated autonomy and responsibility in handling time-sensitive, critical projects
• Prior experience with nTop, parametric CAD, or computational design tools
• Current or recent experience in aircraft conceptual or preliminary design, or a closely related discipline (e.g., aerostructures, propulsion integration, vehicle-level sizing and tradeoff studies, MDO)
• Experience with nTop software or nTop automation (e.g., nTop Automate, headless/CLI execution)
• Experience with GPU-accelerated simulation, cloud/HPC compute orchestration, or physics-ML frameworks (e.g., NVIDIA PhysicsNeMo)
• Experience building or wiring agentic systems (tool calling, MCP servers, workflow orchestration) around engineering software
• Experience in a Solutions, Applications, or Forward Deployed Engineering role at an engineering or AI software company
• Contributions to AI/ML or computational design work through projects, research, open-source work, or technical talks
• Familiarity with Aerospace & Defense engineering programs and digital-engineering practices
• Security clearance, or eligibility to obtain one
• Experience in a fast-paced environment with exposure to GTM/SaaS teams and processes

Qualifications

Must Haves

• A Bachelor's and/or Master's degree in Mechanical, Aerospace, Computational Engineering, or a related engineering discipline, plus 3+ years of industry experience (highly relevant doctoral degrees can be substituted for three years)
• Working knowledge of the aerospace design and analysis toolchain, including at least one of: parametric CAD (CATIA, Siemens NX, SolidWorks, Onshape); FEA (Nastran, Abaqus, Ansys, LS-DYNA); CFD (Fluent/CFX, Star-CCM+, OpenFOAM); conceptual design and MDO tools (OpenVSP, OpenMDAO, ModelCenter, HEEDS, Isight); or PLM (Teamcenter, 3DEXPERIENCE, Windchill)
• Experience scripting in Python, including tools or integrations used by other engineers
• Familiarity with the scientific Python stack (NumPy, SciPy, pandas), LLM APIs, agent frameworks, or tool-calling protocols (e.g., MCP), or at least one ML framework
• Demonstrated ability to learn new technical software quickly
• Systems thinking: able to map how geometry, simulation, data, and AI components fit together across a toolchain and reason about where automation adds the most value
• Excellent communication and presentation skills, with the ability to explain complex topics to technical and non-technical audiences, including large groups and senior-level stakeholders
• Demonstrated autonomy and responsibility in handling time-sensitive, critical projects

Nice to Haves

• prior experience with nTop, parametric CAD, or computational design tools
• Current or recent experience in aircraft conceptual or preliminary design, or a closely related discipline (e.g., aerostructures, propulsion integration, vehicle-level sizing and tradeoff studies, MDO)
• Experience with nTop software or nTop automation (e.g., nTop Automate, headless/CLI execution)
• Experience with GPU-accelerated simulation, cloud/HPC compute orchestration, or physics-ML frameworks (e.g., NVIDIA PhysicsNeMo)
• Experience building or wiring agentic systems (tool calling, MCP servers, workflow orchestration) around engineering software
• Experience in a Solutions, Applications, or Forward Deployed Engineering role at an engineering or AI software company
• Contributions to AI/ML or computational design work through projects, research, open-source work, or technical talks
• Familiarity with Aerospace & Defense engineering programs and digital-engineering practices
• Security clearance, or eligibility to obtain one
• Experience in a fast-paced environment with exposure to GTM/SaaS teams and processes

Benefits

• This role is remote.