{"id":1005989,"url":"https://alion.io/job/aerovect-senior-software-engineer-behavior-planning","title":"Senior Software Engineer, Behavior Planning","company":{"id":4809,"name":"AeroVect","domain":"aerovect.com","url":"https://alion.io/company/aerovect","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":83,"open_postings":6,"ghost_share":0,"stale_share":0.667,"repost_share":0,"time_to_fill_p50_days":45,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Stockholm, Sweden","London, United Kingdom","Berlin, Germany","Amsterdam, Netherlands","Paris, France","Frankfurt am Main, Germany","Munich, Germany","Dublin, Ireland"],"countries":["SE","GB","DE","NL","FR","IE"],"hiring_countries":["US","DE","FR","GB","IE","IT","NL","PL","SE"],"hiring_countries_total":9,"salary":null,"salary_estimate":{"min_usd":95000,"max_usd":194000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"Machine Learning","optional":false},{"name":"Path Planning","optional":false},{"name":"Python","optional":false},{"name":"ROS","optional":false},{"name":"ROS2","optional":false}],"status":"live","first_seen_at":"2026-09-17T15:02:15Z","employer_posted_date":"2026-09-17","last_verified_at":"2026-11-04T15:05:25Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"Who We Are\nAeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.\nWe are looking for an experienced Senior Software Engineer who can design and build best-in-class behavior planning systems for autonomous driving in structured, low-speed environments.\nIn this role, you'll own the design and implementation of key modules in the behavior planner - the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations.\nThis opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team.\nYou Will\nDevelop and implement advanced behavior planning algorithms for autonomous vehicles\n\nCollaborate with cross-functional teams to ensure robust integration and functionality of planning systems\n\nDesign, write, and maintain efficient and scalable code in C++ and Python\n\nContribute to the architecture and continuous improvement of behavior planning software\n\nConduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithms\n\nAnalyze system performance and implement enhancements based on data and feedback\n\nMaintain comprehensive documentation of code, algorithms, and system designs\n\nWork closely with other engineering teams to ensure seamless coordination and development\n\nYou Have\nProficient in modern C++ (11/14/17) and object-oriented programming\n\nSkilled in Python for rapid prototyping and testing\n\nStrong in debugging, profiling, and optimizing code\n\nDeep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning\n\nFamiliarity with path planning algorithms like A*, RRT, or optimization-based methods\n\nMaster’s degree in Computer Science, Robotics, or a related field\n\nMinimum of 3 years of industry experience in autonomous driving, robotics, or a related field\n\nWe Prefer\nKnowledge of state machines, behavior trees, and decision-making under uncertainty\n\nExpertise in path planning algorithms such as A*, D*, and Rapidly-exploring Random Trees (RRT)\n\nKnowledge of machine learning techniques, especially in the context of behavior prediction and planning\n\nExperience with ROS / ROS2\n\nImplementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment\n\nEnsuring that behavior planning algorithms can execute with minimal latency for real-time navigation\n\nProficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty\n\nMaster’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus","description_format":"text","description_chars":3440,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Germany","iso":"DE","kind":"country"},{"name":"France","iso":"FR","kind":"country"},{"name":"United 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