C++ Software Engineer - Mission Systems

Applied Intuition•Columbia, WA

6d•Onsite

About The Position

Applied is seeking a Software Engineer with strong foundations in algorithmic optimization and multi-agent systems. You’ll tackle complex computational challenges in our real-time decision-making platform, designing and implementing advanced algorithms that push the boundaries of autonomous coordination and planning. We seek motivated engineers driven by core mission values to join our Acuity Autonomous Behaviors and Agents engineering team focused on next-generation human-machine teaming and real-time decision-making systems. You’ll help build intelligent agents that plan and execute missions using advanced reasoning, planning, and optimization algorithms. Our work spans real-time scenarios, heterogeneous platforms (air, space, land, surface, sub-surface), and software that integrates seamlessly with human operators. If you thrive in fast-moving, mission-oriented environments and love building autonomy that help our warfighters, this is your role. Your work will support our Axion and Acuity family of systems, enabling breakthrough capabilities in human-machine teaming across all domains. If you’re passionate about applying cutting-edge algorithms to solve mission-critical coordination problems, this role offers exceptional opportunities to advance the state of the art in autonomous decision making systems.

Requirements

BS or MS in Computer Science, Software Engineering, Robotics, or a related technical field, OR 5+ years of professional experience developing intelligent agents or planning systems.
5+ years of hands-on experience developing performant modern C++ (we use C++ 20).
Strong theoretical understanding and practical experience implementing algorithms for constraint satisfaction, scheduling, and optimization problems.
Demonstrable skill in analyzing, visualizing, and optimizing algorithm performance and solution quality.
Proficiency with Bazel in Docker-based Linux environments.
Strong procedural and object-oriented programming experience that employs clean code principles and good OOP design patterns/principles.
Experience developing in Docker and containerized development environments, and using Linux-based operating systems (e.g., RHEL, Ubuntu).
Understanding of Service-oriented Architecture and message broker vs data broker paradigms.
Experience using git, Visual Studio Code, GitLab, SonarQube, and Artifactory or Azure Container registry.
Ability to translate complex mathematical concepts into clear technical documentation and communicate complex software designs.
Strong critical thinking skills, methodical approach to algorithm development and validation, and ability to thrive in a dynamic, fast-paced environment.
Excellent analytical, communication, and documentation skills with demonstrated ability to collaborate across multiple teams.
Passion for solving complex problems with little supervision in a fast-moving team.
Ability to balance multiple priorities in a fast-paced, highly collaborative, frequently changing, and sometimes ambiguous environment.
Occasional travel required (approx. 10–20%) for demonstrations, integration, or customer engagement
Must be a U.S. Citizen
Must be eligible for a U.S. SECRET clearance with Special Access Program (SAP) eligibility

Nice To Haves

Advanced degree (MS+) in algorithms, computational optimization, or autonomous systems, OR 5+ years building autonomous decision systems.
Expertise in advanced planning paradigms (e.g., PDDL, HTN planning, Monte Carlo tree search), temporal reasoning, formal verification, or symbolic planning.
Experience with game theory for multi-agent coordination or negotiation protocols.
Familiarity with real-time optimization under hardware/edge constraints.
Background in Battle Management Command and Control (BMC2) or defense applications.
Master’s degree in computer science/related engineering field.
7+ years developing software in C++ (C++ 2017)
Proficient with build tools like Conan and Bazel.
Experience on national security projects for government agencies.
Interdisciplinary background with a focus on continual learning.

Responsibilities

Design and implement multi-agent optimization algorithms for distributed decision-making and coordination problems
Develop temporal logic frameworks and constraint-satisfaction algorithms for complex planning scenarios
Create mathematical models for sequential decision process under uncertainty with probabilistic outcomes
Build computational frameworks that balance algorithmic efficiency with human-interpretable reasoning
Implement and evaluate quantitative metrics for algorithm performance, solution quality, and computational efficiency
Translate theoretical approaches into production-ready software implementations with rigorous testing methodologies
Collaborate with cross-disciplinary teams to refine algorithmic approaches based on empirical evaluation
Communicate technical details effectively across stakeholders, sponsors, and leadership