Project description We are looking for a Simulation & Autonomy Systems Architect to join a senior Grid Dynamics architecture team on a construction-autonomy (physical AI) program at a general heavy-equipment manufacturer. The program's goal is autonomous machines that operate unsupervised at customer sites. One data loop ties the program together. Sensor kits on the machines collect site data, a cloud platform curates and annotates it, and the result trains end-to-end vision-language-action (VLA) robotics models and feeds simulation. The trained models then run back on the machines. The data-collection fleet is growing to a large scale. Our architects work embedded in the client's program across three functions: on-machine perception and data collection, data platform, and robotics and autonomy (behavior, control and safety). They also co-author the program charter and roadmap with the client. Teams are execution-first and hands-on: architecture is expected to turn into working software quickly, and engineering works with AI coding agents.

Requirements:
• 10+ years in robotics or autonomous systems, with hands-on ownership of behavior, planning or control software in a deployed autonomy stack (robotaxi, autonomous trucking, mining, agriculture, construction or similar).
• Proven design of fault detection, degraded modes, minimum-risk maneuvers and fallback behavior in a fielded system.
• Experience integrating simulation into the autonomy development and validation loop, including scenarios, sensor models and data contracts between simulation and the stack (NVIDIA Isaac Sim, CARLA or equivalent).
• Experience leading FMEA,



fault-tree or hazard analysis with functional safety teams under ISO 26262, ISO 21448 (SOTIF), ISO 17757, IEC 61508 or an equivalent standard.
• Real-time software architecture on embedded compute, including hardware/software integration.
• Writes production code in C++ and Python, and is comfortable working with AI coding agents. Nice-to-have
• Heavy-duty or off-road autonomy (trucks, mining, construction or agricultural machines), including vehicle dynamics under load and on rough terrain.
• End-to-end learned driving or VLA models, and how to wrap them in safety envelopes.
• NVIDIA Omniverse and synthetic data generation for training and testing.

Responsibilities:
As the Simulation & Autonomy Systems Architect in the robotics and autonomy function, you will cover simulation, behavior, control and system safety, working closely with the perception team.
• Own the program's simulation strategy: how simulation feeds autonomy development and validation, scenario coverage, and how real and simulated data are combined.
• Lead system-wide failure analysis (FMEA and fault-tree analysis) across perception, planning, control and hardware, from the early stages rather than after launch.
• Design degraded modes and minimum-risk conditions, including health monitors, run levels,



fail-operational versus fail-safe behavior, and fallback paths a simpler system can follow.
• Architect fast reactive safety layers, such as collision-imminent braking that doesn't wait on the full perception pipeline, while keeping false positives low.
• Own system-level hardware/software architecture across teams, and advise hardware teams on which requirements must be fixed now and which can wait.
• Build the safety case with the safety engineering team, defining acceptable event rates for a given fleet size and operating hours, and the signals that demonstrate due diligence.
• Write, review and guide code produced with AI coding agents, within guardrails such as automated tests and toolchain checks.
• Lead the workstream's contribution to the program charter and roadmap, guide the team's simulation and perception architects, and mentor engineers by example.

About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

📌 Simulation & Autonomy Systems Architect (España)
🏢 Grid Dynamics
📍 España