Principal Radar Signals Engineer

Description

SAIC is hiring a Radar Signals Engineer to join a mission-driven, multi-disciplinary analysis team in Chantilly, VA, supporting multiple satellite programs at the forefront of national innovation. This role focuses on modeling, simulation, and analysis of target-tracking radar systems for satellites across all Earth orbits, directly supporting high-visibility national priorities. You will work in a secure Government environment with frequent access to senior Government decision-makers and daily collaboration with experts in propulsion, radars, optics, AI/ML, cloud computing, GPUs, and more.

Responsibilities include, but are not limited to:

• Design and analyze satellite-tracking radar waveforms and signal processing algorithms for detection, acquisition, tracking, and characterization of space targets.
• Perform radar and antenna performance analyses, including link budgets and tracking performance across LEO, MEO, & GEO.
• Develop and execute modeling and simulation of radar-to-satellite engagement scenarios, including optional radar return modeling using 3D satellite models.
• Use programming languages such as Python, C++, MATLAB, or similar tools to implement, validate, and enhance models, simulations, and data-processing pipelines.
• Conduct independent trade studies and technical assessments of radar architectures, algorithms, and system performance, including review and validation of algorithms and results produced by external teams.
• Document findings and develop actionable technical briefings, with opportunities to present results to senior Government stakeholders.

Qualifications

• Bachelor's degree in Electrical Engineering, Applied Mathematics, Physics, or a related technical field and 9+ years of relevant experience; OR
• Master's degree in a related technical field and 7+ years of relevant experience; OR
• PhD or JD in a related field and 4+ years of relevant experience.
• Demonstrated experience with target-tracking radar signals, including waveform design, detection/tracking algorithms, or target characterization.
• Strong foundation in electrical engineering, advanced mathematics, and digital signal processing (DSP).
• Proficiency with Python, C++, MATLAB, or similar languages for modeling, simulation, and analysis of radar or signal processing problems.
• Ability to work effectively in a collaborative, multi-disciplinary team and clearly communicate complex technical concepts in written reports and oral briefings.

Clearance Requirements:

• Active TS/SCI clearance is required.
• Must have, or be willing and able to successfully complete, a polygraph examination as required by the customer.
• Must be willing and able to work on-site in Chantilly, VA, within a secure Government environment.

Preferred Qualifications:

• Experience with space domain awareness (SDA), satellite tracking, or radar systems specifically designed for space targets or long-range surveillance.
• Background in antenna design, RF/microwave engineering, or radar system architecture and performance modeling.
• Familiarity with orbital mechanics/astrodynamics and modeling satellites in LEO/MEO/GEO or other orbital regimes.
• Experience leveraging high performance computing (HPC), GPU-accelerated processing, or cloud environments for large-scale modeling and simulation.
• Prior experience supporting Government or DoD/IC customers and presenting technical findings to senior stakeholders.
• Active TS/SCI with a Polygraph

Physical Requirements:

• Work is primarily performed in an office or laboratory environment within a secure facility.
• Must be able to sit or stand at a computer workstation for extended periods while performing modeling, simulation, and analysis tasks.
• Occasional movement between offices, conference rooms, and secure work areas is required.
• Ability to lift and carry up to 20 pounds of laptops, documents, or small equipment as needed.

2026.10.1

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.