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Key Responsibilities and Required Skills for Virtual Program Engineer

💰 $ - $

EngineeringAutomotiveAerospaceSimulationCAEProduct Development

🎯 Role Definition

At the heart of modern product development, the Virtual Program Engineer (VPE) is a pivotal technical leader who drives the design and validation process using advanced digital tools. This role acts as the central hub for all virtual simulation activities for a specific product or program. The VPE translates physical product requirements into a comprehensive virtual test plan, orchestrates multi-disciplinary simulations (like crash, durability, and NVH), and synthesizes the results into actionable design guidance. By "building" and "testing" the product in the digital world first, the VPE enables the organization to identify design flaws, optimize performance, and reduce reliance on costly and time-consuming physical prototypes, ultimately accelerating the product's journey to market.

📈 Career Progression

Typical Career Path

Entry Point From:

  • CAE Analyst / Simulation Engineer
  • Product Design Engineer with a strong analytical focus
  • Test and Validation Engineer

Advancement To:

  • Senior or Lead Virtual Program Engineer
  • CAE or Simulation Manager
  • Chief Engineer - Virtual Engineering & Digital Twin
  • Systems Engineering Manager

Lateral Moves:

  • Product Development Lead
  • Systems Integration Engineer
  • Technical Project Manager

Core Responsibilities

Primary Functions

  • Develop and execute a comprehensive virtual validation plan (DVP&R) for the entire vehicle or subsystem program, aligning with key program milestones and physical test plans.
  • Lead the integration of multi-disciplinary CAE models, including structures, safety, NVH, durability, and thermal, to create a holistic virtual prototype of the product.
  • Perform in-depth analysis and post-processing of complex simulation results to deliver clear, concise, and actionable recommendations for design improvements to the engineering teams.
  • Act as the primary technical point of contact for all simulation-related activities within the program, effectively communicating status, risks, and opportunities to leadership and cross-functional teams.
  • Drive the correlation process between virtual simulation models and physical test data, continuously refining model accuracy and predictive capability.
  • Champion the use of virtual engineering methodologies to influence design direction early in the development cycle, preventing costly late-stage engineering changes.
  • Build, manage, and maintain highly detailed and complex CAE system and subsystem models for analysis, ensuring high levels of quality and fidelity.
  • Proactively identify potential design and performance issues through simulation, and lead cross-functional problem-solving sessions to develop and verify robust solutions.
  • Develop and implement new simulation techniques, processes, and methodologies to enhance the team's capabilities and improve overall efficiency.
  • Generate and present comprehensive technical reports and presentations that clearly articulate simulation findings and their impact on product performance to a diverse audience.
  • Collaborate closely with CAD designers to provide upfront feedback on design for manufacturability, performance, and mass optimization based on simulation insights.
  • Manage the balance between simulation model fidelity, computational cost, and program timing to ensure timely delivery of results that meet decision-making needs.
  • Define and cascade performance targets from the vehicle level down to the component level, ensuring all subsystems contribute to the overall program objectives.
  • Coordinate the activities of supporting CAE analysts and external partners to ensure all simulation tasks are completed on time and to the required quality standards.
  • Interpret and apply regulatory requirements (e.g., FMVSS, ECE) and consumer-facing ratings (e.g., IIHS, NCAP) within the virtual simulation environment to predict compliance and performance.
  • Lead virtual design of experiments (DOE) and optimization studies to explore the design space, identify optimal solutions, and understand performance trade-offs.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis to investigate novel design concepts or unexpected field issues.
  • Contribute to the organization's long-term data and digital twin strategy and help define the roadmap for future virtual engineering tools and infrastructure.
  • Collaborate with business units, marketing, and product planning to translate future customer needs and market trends into tangible engineering requirements for simulation.
  • Participate in sprint planning, retrospectives, and other agile ceremonies within the broader product development team to ensure alignment and continuous improvement.
  • Mentor junior engineers and new hires, providing guidance on best practices, tool usage, and the interpretation of simulation results.
  • Stay abreast of emerging technologies, academic research, and competitive trends in the virtual engineering, simulation, and high-performance computing (HPC) space.
  • Assist in the development of CAE automation scripts and workflows to streamline repetitive tasks and improve overall team productivity.

Required Skills & Competencies

Hard Skills (Technical)

  • CAE Pre/Post-Processing: High-level proficiency with industry-standard tools such as HyperMesh, ANSA, Simcenter 3D, or Abaqus/CAE for complex model build and results interpretation.
  • FEA Solver Expertise: Deep knowledge and hands-on experience with one or more major FEA solvers, such as LS-DYNA, Abaqus, Nastran, ANSYS, or OptiStruct.
  • Multi-Disciplinary Knowledge: Strong foundational understanding of various engineering disciplines, including crashworthiness/safety, NVH (Noise, Vibration, and Harshness), structural durability, and statics.
  • CAD Integration: Familiarity with major CAD platforms (CATIA, Siemens NX, Creo) for geometry cleanup, manipulation, and integration with CAE models.
  • Scripting & Automation: Practical ability to write scripts for process automation and data analysis using languages like Python, MATLAB, or TCL.
  • Optimization Techniques: Experience with design optimization tools (e.g., HEEDS, Isight, ModeFRONTIER) and a solid understanding of Design of Experiments (DOE) methodologies.
  • Data Visualization: Skill in using post-processing tools (HyperView, MetaPost, EnSight) to create compelling visualizations that communicate complex engineering phenomena.
  • HPC Environment: Comfortable working in a High-Performance Computing (HPC) environment and using Linux/Unix-based systems for job submission and management.

Soft Skills

  • Analytical Problem-Solving: An innate ability to deconstruct complex technical problems, analyze data from multiple sources, and formulate robust, physics-based conclusions.
  • Influence & Communication: Excellent verbal and written communication skills, with the ability to confidently present technical findings and influence decisions among engineers, managers, and executives.
  • Cross-Functional Collaboration: A collaborative mindset with a proven ability to work effectively with diverse teams, including design, testing, manufacturing, and program management.
  • Project & Time Management: Strong organizational skills to manage multiple simulation tasks simultaneously, prioritize work based on program needs, and deliver results under tight deadlines.
  • Intellectual Curiosity: A proactive and self-motivated drive to continuously learn, question assumptions, and explore innovative ways to apply virtual tools to solve engineering challenges.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor of Science (B.S.) in a relevant engineering discipline.

Preferred Education:

  • Master of Science (M.S.) or Doctorate (Ph.D.) with a specialization in Computational Mechanics, Finite Element Analysis, or a related simulation-focused field.

Relevant Fields of Study:

  • Mechanical Engineering
  • Aerospace Engineering
  • Automotive Engineering
  • Engineering Mechanics

Experience Requirements

Typical Experience Range:

  • 3-8 years of progressive experience in a CAE, simulation, or analytical product development role.

Preferred:

  • Direct experience leading virtual validation activities for a major subsystem or full vehicle program within the automotive, aerospace, or heavy equipment industry.
  • A demonstrated track record of successfully correlating simulation predictions with physical test data and using the results to drive design changes.
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