Principal Application Engineer - Missile Defense

**Please note that this role can be based in any of the following locations: Colorado Springs, CO, Washington, DC area, Huntsville, AL, Exton, PA

We Are

Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.

You have spent a decade or more working at the intersection of missile defense physics, sensor phenomenology, and simulation environments that actually get used to make decisions. You understand that the difference between a training dataset that works and one that misleads an AI model comes down to how well you represent real-world sensor behavior, including the messy edge cases most people ignore.

You think in kill chains, not just models. You know what happens when a missile stages, what that looks like to an X-band radar versus an IR sensor, and why those distinctions matter when someone downstream is building a discrimination algorithm or a battle management system. You have worked with real radar data or EO/IR systems, not just textbook examples, and you can translate that experience into high-fidelity simulations that hold up under scrutiny.

You are comfortable working in environments where the requirements evolve as the threat does. You do not wait for perfect specifications. You ask the right questions, align with subject matter experts, and build something that works now while staying flexible enough to adapt later. At Synopsys Government Initiatives, you will work on simulation environments that directly support the defense community's ability to detect, track, and respond to real threats.

• Build and refine high-fidelity models of threat trajectories, missile staging events, and multi-spectral signatures (RF, IR, and beyond) within air and missile defense simulation environments
• Develop radar phenomenology models that represent how different sensor architectures and bands observe and interpret target behavior across the kill chain
• Create synthetic datasets for AI/ML training that include realistic sensor observations, target-present and target-absent scenarios, and edge cases that reduce algorithmic bias
• Integrate signature simulation capabilities into frameworks like STK and AFSIM to support threat detection, tracking, discrimination, and battle management decision support
• Collaborate with government labs, defense research facilities, and internal subject matter experts to ensure simulation fidelity matches real-world sensor and threat behavior
• Support the design and implementation of track fusion, custody management, and sensor integration functions across complex missile defense architectures
• Provide technical leadership on modeling requirements, simulation accuracy, and emerging program needs involving generative simulation of sensing systems

• Enable next-generation AI/ML systems to train on datasets that reflect real-world sensor complexity, improving detection and discrimination performance in operational environments
• Deliver simulation environments that support critical experimentation, algorithm evaluation, and system development for air and missile defense programs
• Reduce the time and cost required to generate high-fidelity training data by automating signature modeling and sensor observation workflows
• Improve the accuracy of threat modeling and sensor simulation, giving defense decision-makers better tools to evaluate system performance before deployment
• Bridge the gap between physics-based modeling and operational battle management concepts, ensuring simulations reflect how systems actually work in the field
• Contribute to the development of frameworks that support multi-domain sensing, track fusion, and custody management across the missile defense kill chain
• Influence the technical direction of emerging programs by defining modeling standards, fidelity requirements, and integration approaches

• BS in Engineering, Physics, Computer Science, or related field with 10+ years of professional experience, or MS with 8+ years (PhD with 7+ years preferred)
• This position requires a government Top Secret or TS/SCI security clearance. You must be a U.S. citizen for consideration.
• Deep experience in air and missile defense systems, including sensor architectures and threat modeling
• Strong understanding of sensor phenomenology and signature modeling across RF and IR spectra, with exposure to real-world radar or EO/IR systems and data
• Proficiency in MATLAB or Python for modeling, scripting, and interfacing with DoD systems
• Experience with Systems Tool Kit (STK) and Advanced Framework for Simulation, Integration and Modeling (AFSIM) is highly desirable
• Ability to travel domestically up to 25% of the time

• You can explain a complex radar phenomenology tradeoff to a program manager in two sentences without losing the technical nuance, and you know when to dig deeper
• You have worked with real sensor data before, not just simulations, and you understand the difference between what a model predicts and what a sensor actually sees
• You are comfortable operating in environments where the threat evolves faster than the documentation, and you know how to build models that stay relevant
• You manage multiple technical threads at once without losing track of the bigger picture, whether that is a kill chain architecture or an AI training pipeline
• You push back when a modeling assumption does not match reality, and you bring alternatives instead of just problems
• You thrive in roles where your technical depth directly supports operational decision-making, not just research for its own sake

You will join the Ansys Customer Excellence (ACE) team within Ansys Government Initiatives (AGI), supporting advanced modeling and simulation efforts for space, air, and missile defense systems. This team works closely with government labs, defense research facilities, and operational communities to deliver simulation environments that support system development, algorithm evaluation, and AI/ML training. Your recruiter will share more about the team structure, current projects, and collaboration model during the interview process.

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