Senior C++ Software Engineer (Defense Autonomy)
About The Position
Applied Intuition is seeking a Software Engineer with strong foundations in algorithmic optimization and multi-agent systems to tackle complex computational challenges in their real-time decision-making platform. The role involves designing and implementing advanced algorithms for autonomous coordination and planning, focusing on next-generation human-machine teaming and real-time decision-making systems. The engineer will help build intelligent agents that plan and execute missions using advanced reasoning, planning, and optimization algorithms, working with real-time scenarios, heterogeneous platforms (air, space, land, surface, sub-surface), and software that integrates seamlessly with human operators. This role supports the Axion and Acuity family of systems, enabling breakthrough capabilities in human-machine teaming across all domains. The position offers 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++ (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.
- 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
Benefits
- Comprehensive health, dental, vision, life and disability insurance coverage
- 401k retirement benefits with employer match
- Learning and wellness stipends
- Paid time off
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Associate degree
