Senior C++ Software Engineer (Collaborative Autonomy)

Applied IntuitionPoway, CA
$150,000 - $225,000Onsite

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.
  • Ability to translate complex mathematical concepts into clear technical documentation and communicate complex software designs.
  • 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.

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

Benefits

  • equity in the form of options and/or restricted stock units
  • 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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