Founding Engineer, Robot Behavior and Decision-Making

The Bigger PictureAt Andromeda, we're building the social intelligence layer for humanoid robots - technology that allows robots to understand people, build relationships and become a meaningful part of everyday life.Our first robot, Abi, is already doing this in aged care and healthcare, where she brings conversation, companionship and engagement to people every day.Now we're scaling from early deployments into a platform that can operate across thousands of real-world environments. We're looking for individuals who want to tackle hard problems across robotics and AI, and help define what it means for robots to live and interact alongside people.The RoleWe are looking for an engineer to found our Mission Autonomy team, which will own our robot's long-duration decision-making layer and orchestrate the totality of Abi's day. Mission Autonomy continuously decides what Abi should do next, balances task-level trade-offs, and adapts the robot's plan across an eight-hour shift. It sits above and orchestrates Abi's existing layers that perform conversations, waypoint navigation and obstacle avoidance, perception, gestures, and operator tooling.As the founding Mission Autonomy team member, you will propose and build Andromeda's Mission Autonomy (MA) architecture from the ground up, using frontier models and evaluation (both sim and real-world) to train and launch MA, and work with our voice agent, mobile autonomy, and gestures teams to design harnesses through which MA can execute behaviors on Abi. Once built, MA should guide Abi through a home, choose when to join an interaction, keep her character, and recover when the plan breaks. There is no playbook for this. You'll need a keen eye for model evaluation and trade-offs, balancing architectural leadership with strategic hands-on work. The work combines research with practical robotics.Key ResponsibilitiesDesign the system. Challenge our initial concepts as you discover what a full shift actually needs: is it formulated as an agent harness ingesting scene graphs and acting over robust, typed action primitives? Or will you invoke World Models and VLA components? You will shape the Mission Autonomy roadmap for AndromedaPrototype the system. Get a mission autonomy loop running in simulation early. Use it to decide what we build, before the company commits teams to an architectureCo-design and build simulation capabilities with our simulation engineerOwn the technical direction and run the design conversations with autonomy, chatbot, perception, audio and platform teams. Turn them into contracts those teams can build againstShape the action primitives. Work out what the mission needs from the layers underneath. Specify it properly. Get it built, whether that means convincing the owning team or writing it yourselfDesign for degradation. Define how Abi should behave when audio, perception, connectivity, navigation, or platform health degrades. Make those moments safe, useful, and legible to operators, while preserving Abi's character rather than treating every failure as a generic error stateEstablish deployment patterns. Create a repeatable path from simulation prototypes to demonstrations on the robot, with the configuration, observability, test gates, and rollback mechanisms needed to iterate safelyBuild the evaluation system. Define benchmarking protocols, evaluation methods, and reporting that let us continuously measure the longest-horizon missions Abi can complete, the interventions they require, and the failure modes that limit themYour first 90 daysMonth 1: Learn about Abi in the real world: read the Concept of Operations document, challenge its assumptions, and spend time with Abi in an aged-care home. Bring the autonomy, conversational AI, perception, audio, platform, and simulation teams together to define how the system makes decisions and how the layers work together. Deliver the first architecture and a clear six-month build plan, including what not to build.Month 2: Build a working slice in simulation: Abi drives to a resident's room, arrives safely, and starts a conversation. Use simulation to discover what breaks when the resident is absent, the route changes, or a subsystem degrades. Turn those lessons into better interfaces, a repeatable evaluation harness, and the next set of hypotheses and assumptions to test.Month 3: Take the prototype from simulation to Abi in the lab. Establish the deployment, monitoring, replay, and evaluation patterns that show how far Abi can run autonomously, what stops her, and why.RequirementsSkills and Experience Required5+ years of experience building autonomous systems, with an MS or PhD in Robotics, Computer Science, or a related field, or equivalent practical experiencePrevious autonomy experience in areas such as self-driving, mobile robotics, warehouse robotics, field robotics, or similar, including at least one deployment lifecycle from concept through deployment and operationsExperience with ROS 2, Nav2, and simulation tools such as Isaac Sim, Gazebo, or MuJoCoAwareness of safety-critical design principles for robots operating around peopleStrong software engineering skills in Python, C++, or Rust. Comfortable working across the stack, from high-level planning and behavior to low-level robot interfaces and runtime constraintsPractical robotics experience. Comfortable bringing up hardware, debugging sensors and actuators, and tinkering with the robot in the officeStrong communication and influence skills, particularly when working across Australian teams and with engineers whose systems you do not directly ownArchitecture and software depth. Able to steer the system design, define interfaces and contracts, and write the first versions of the primitives rather than wait for another teamBonus pointsExperience building mission autonomy systems in robotics, defense technology, or similar domains. Research experience, ideally at master's or PhD level, applying LLM techniques to long-duration robotic task planning, orchestration, tool use, or error recoveryExperience designing simulation-based evaluation systems, including benchmarks, scenario harnesses, metrics, failure taxonomies, and reporting for long-horizon missionsExperience with robot planning and behavior architectures, including Planning Domain Definition Language (PDDL), task-and-motion planning, behavior trees, or finite-state machines for baseliningTechnical judgment. Able to reason about trade-offs explicitly, and earn the trust of senior autonomy engineers and the teams that own adjacent parts of the stackBenefitsThe expected base salary for this role is $200,000 to $240,000 USD. Actual compensation will be determined by a variety of factors, including the candidates' job related knowledge, skills and experience.If you're excited about this role but don't meet every requirement, that's okay; we still encourage you to apply. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.Our ValuesEmpathy - Kindness and compassion are at the heart of everything we doPlay - Play sharpens focus. It keeps us curious, fast and obsessed with the craftNever Settle - A relentless ambition, bias toward action, and uncomfortable levels of curiosityTenacity - Tenacious under pressure, we assume chaos and stay in motion to adapt and progressUnity - Different minds. Shared mission. No passengersLet's build the future together.Please note: At this time, we are generally not offering visa sponsorship for this role.