Job description

Build the simulated worlds where autonomous UUVs learn, fail, improve, and prove they’re ready for the real one. Leidos is looking for an Autonomous Simulation Software Engineer to build the software and simulation infrastructure behind next-generation uncrewed underwater vehicles and maritime autonomous systems. Autonomous systems operating underwater face a uniquely unforgiving environment: limited communications, uncertain navigation, imperfect sensors, complex vehicle dynamics, and missions where the software must make good decisions without waiting for help. We need simulation environments capable of reproducing those challenges with enough fidelity to develop, integrate, test, and ultimately trust the autonomy that operates in them. This is a hands-on software engineering role for someone who enjoys building simulators, modeling complex systems, and creating reusable simulation frameworks. You’ll develop software that models vehicles, sensors, environments, interfaces, faults, and behaviors—giving engineers the ability to exercise mission software repeatedly before putting a vehicle in the water. You’ll directly support a growing programwhile also helping evolve and expand our MAGMA-based Simulation Framework, creating simulation capabilities that can be reused across vehicles, missions, and programs. We already have engineers who know autonomy and engineers who have built simulation capability out of necessity. We’re looking for someone who brings simulation engineering as a discipline—and who wants to help us take that capability much further. Why This Role Is Different You’ll build simulations that engineers actually depend on , not visualization demos. You’ll model real systems and real failure modes , including vehicles, sensors, environments, interfaces, and mission behaviors. You’ll help increase simulation fidelity , closing the gap between what happens in software and what happens when a vehicle enters the water. You’ll shape a growing simulation framework , not simply write scenarios against a finished product. You’ll work directly with autonomy and vehicle engineers , using simulation to find problems earlier and accelerate development. You’ll have room to experiment , developing new approaches for modeling, simulation, test, and analysis that can grow beyond a single program. If you enjoy building software that recreates complicated real-world systems—and seeing that software make an engineering team faster and a deployed system more reliable—this is the role. Primary Responsibilities Build high-fidelity simulation software using modern C , Java, and Python on Linux-based systems to model autonomous vehicles, sensors, environments, interfaces, and mission behavior. Expand and evolve our MAGMA-based Simulation Framework , developing reusable simulation components, interfaces, models, tooling, and architectural patterns that can support multiple vehicles and programs. Increase simulation fidelity by working with autonomy, systems, hardware, and test engineers to identify the behaviors and interactions that matter most and represent them effectively in software. Model complex systems and behaviors , translating vehicle characteristics, sensor behavior, environmental effects, system interfaces, and operational constraints into useful software models. Enable autonomy development and test , creating simulation environments where mission software can be exercised repeatedly across nominal, edge-case, degraded, and failure scenarios before deployment to real hardware. Architect scalable simulation infrastructure , emphasizing modularity, extensibility, deterministic behavior where appropriate, performance, and reuse across different platforms and levels of simulation fidelity. Connect simulation to production software , integrating simulated components with real autonomy and mission software through representative interfaces and protocols. Build tools that accelerate engineering , including scenario generation, instrumentation, data collection, playback, debugging, visualization, and automated simulation execution. Validate simulation against reality , using test data, system behavior, and engineering analysis to understand where models are representative—and where they are not. Ship real capabilities , developing, integrating, testing, and maintaining production-quality simulation software with ownership from architecture through implementation and use. Collaborate across disciplines , contributing to technical debates, design reviews, and trade studies involving autonomy, systems engineering, vehicle software, hardware, modeling, and test. Continuously improve how we simulate and test , helping establish simulation engineering practices that increase development velocity without sacrificing technical rigor. Basic Qualifications Education & Experience — Bachelor’s degree in Computer Science, Software Engineering, Robotics, Engineering, or a related field with 8–12 years of experience, or a Master’s degree with 6–10 years of experience. Security Eligibility — Must have a current, active Secret clearance . Serious C Skills — Demonstrated experience developing modern C software on Linux, with strong fundamentals in software architecture, performance, memory management, debugging, and code quality. Simulation Software Experience — Experience developing software used to simulate, model, emulate, or test complex physical or cyber-physical systems. Systems Thinking — Ability to understand how software components interact with sensors, hardware, networks, physical systems, and their operating environment—and translate those interactions into useful simulation abstractions. Engineering Judgment — Ability to choose the right level of fidelity for the engineering problem rather than simply maximizing model complexity. Software Architecture — Experience designing modular, extensible software systems with well-defined interfaces that can evolve as requirements and modeled systems change. Modern Development Environments — Experience developing and deploying software in Linux and virtualized or containerized environments such as VMware or Docker. Test & Analysis Mindset — Ability to design simulations and tests that expose meaningful system behavior, investigate unexpected results, and distinguish software defects from modeling limitations. Clear Communication — Ability to explain complex technical ideas and modeling assumptions to software, systems, hardware, test, and program stakeholders. Professional Integrity — Ownership, accountability, intellectual curiosity, and respect for teammates and mission outcomes. Preferred Qualifications Robotics & Autonomy — Hands-on experience with autonomous systems, robotics, decision-making, planning, navigation, controls, or mission-management software. Vehicle Simulation — Experience modeling robotic vehicles, dynamics, sensors, actuators, navigation systems, communications, or environmental interactions. SIL/HIL Experience — Experience developing or integrating Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), or other simulation and test environments. Simulation Architecture — Experience developing reusable simulation frameworks rather than only creating individual models or scenarios. Model Validation — Experience comparing simulated behavior against real-world data and identifying appropriate fidelity, assumptions, uncertainty, and limitations. Scenario & Monte Carlo Testing — Experience creating automated scenarios, parameter sweeps, Monte Carlo analysis, fault injection, or large-scale simulation campaigns. Distributed Simulation — Experience with simulation systems composed of multiple processes, nodes, services, or federated components operating through realistic interfaces. Polyglot Engineering — Experience across multiple languages such as C#, Java, Python, or Rust and comfort adapting to new stacks quickly. Embedded or Low-Level Experience — Exposure to embedded systems, resource-constrained environments, real-time systems, or software interacting directly with vehicle hardware. Legacy-to-Modern Skill — Experience diagnosing, refactoring, and improving large or aging codebases while preserving working capabilities. Maritime or Undersea Experience — Background with autonomous, remotely operated, or mission-critical platforms, particularly UUVs, AUVs, ROVs, or other maritime systems. Systems Engineering Familiarity — Familiarity with MBSE concepts and tools such as Cameo or MagicDraw and the relationship between system models, software architecture, simulation, verification, and validation. Toolchain Familiarity — Experience with ROS, Protocol Buffers, SCons, VS Code, CI/CD systems, and cross-platform build environments is a strong plus. SUBSEAMSS If you re looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We re not hiring followers. We re recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We re already at step 30 — and moving faster than anyone else dares. Original Posting: August 19, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $131,300.00 - $237,350.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

Requirements

Must-haves

Build the simulated worlds where autonomous UUVs learn, fail, improve, and prove they’re ready for the real one.
Leidos is looking for an Autonomous Simulation Software Engineer to build the software and simulation infrastructure behind next-generation uncrewed underwater vehicles and maritime autonomous systems.
You’ll directly support a growing programwhile also helping evolve and expand our MAGMA-based Simulation Framework, creating simulation capabilities that can be reused across vehicles, missions, and programs.
Why This Role Is Different
You’ll build simulations that engineers actually depend on , not visualization demos.
You’ll model real systems and real failure modes , including vehicles, sensors, environments, interfaces, and mission behaviors.
You’ll help increase simulation fidelity , closing the gap between what happens in software and what happens when a vehicle enters the water.
You’ll shape a growing simulation framework , not simply write scenarios against a finished product.
You’ll work directly with autonomy and vehicle engineers , using simulation to find problems earlier and accelerate development.
You’ll have room to experiment , developing new approaches for modeling, simulation, test, and analysis that can grow beyond a single program.
If you enjoy building software that recreates complicated real-world systems—and seeing that software make an engineering team faster and a deployed system more reliable—this is the role.
Build high-fidelity simulation software using modern C , Java, and Python on Linux-based systems to model autonomous vehicles, sensors, environments, interfaces, and mission behavior.

Nice-to-haves

Robotics & Autonomy — Hands-on experience with autonomous systems, robotics, decision-making, planning, navigation, controls, or mission-management software.
Vehicle Simulation — Experience modeling robotic vehicles, dynamics, sensors, actuators, navigation systems, communications, or environmental interactions.
SIL/HIL Experience — Experience developing or integrating Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), or other simulation and test environments.
Simulation Architecture — Experience developing reusable simulation frameworks rather than only creating individual models or scenarios.
Model Validation — Experience comparing simulated behavior against real-world data and identifying appropriate fidelity, assumptions, uncertainty, and limitations.
Scenario & Monte Carlo Testing — Experience creating automated scenarios, parameter sweeps, Monte Carlo analysis, fault injection, or large-scale simulation campaigns.
Distributed Simulation — Experience with simulation systems composed of multiple processes, nodes, services, or federated components operating through realistic interfaces.
Polyglot Engineering — Experience across multiple languages such as C#, Java, Python, or Rust and comfort adapting to new stacks quickly.
Embedded or Low-Level Experience — Exposure to embedded systems, resource-constrained environments, real-time systems, or software interacting directly with vehicle hardware.
Legacy-to-Modern Skill — Experience diagnosing, refactoring, and improving large or aging codebases while preserving working capabilities.
Maritime or Undersea Experience — Background with autonomous, remotely operated, or mission-critical platforms, particularly UUVs, AUVs, ROVs, or other maritime systems.
Systems Engineering Familiarity — Familiarity with MBSE concepts and tools such as Cameo or MagicDraw and the relationship between system models, software architecture, simulation, verification, and validation.

Application prep

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Keywords to mirror

javapythondockerrustci/cd

Platform: workday
Effort: long