• Establish yourself as the engineer others look to when the problems are the hardest and make sure they come away knowing how to approach the next one themselves. • Lead API surface decisions: what gets exposed, what stays internal, what the stability guarantees are for external consumers. • Own technical discovery for new capabilities; work with product and clinical stakeholders to translate requirements into feasible contracts. • Participate in on-call rotation for the Synapse Everywhere platform; respond to incidents, own post-incident reviews, and drive reliability improvements from what is learned. • Provide expert code reviews and technical mentorship within the team. • Design solutions on modern infrastructure (cloud solutions, k8s, LLMs) with expert level understanding of what and why, not just being able to call infrastructure or run pipelines.

• Develop and own vehicle dynamics models, including high-fidelity truck models that accurately represent longitudinal, lateral, and transient behavior for use in simulation and autonomy validation • Design, develop, and maintain high-fidelity simulation platforms used to validate autonomous driving software in closed-loop evaluation pipelines at scale • Partner with autonomy engineering teams to capture and implement vehicle model requirements that support planning, controls, and system-level V&V activities • Own model capability communication, known limitations, and release notes to enable effective autonomy validation • Ensure vehicle model updates do not regress autonomy V&V system performance by using automated regression frameworks • Execute full software development lifecycle activities primarily in C++ within a Linux development environment and ROS/ROS2 tooling, applying Lean-Agile methodologies • Perform root cause analysis on issues identified during simulation runs and hardware-in-the-loop testing • Participate in designing test plans for data acquisition and telemetry that support field data collection for vehicle model refinement • Support system-level test plans and verification strategies • Communicate progress, design decisions, and blockers clearly at daily stand-ups and design reviews • Build and maintain collaborative relationships with OEM partners and simulation tool vendors to evaluate, integrate, and co-develop simulation capabilities

• Help set technical direction for the ControlCheck team, designing work that spans multiple domains (front-end, back-end, infrastructure) over months, not sprints • Contribute to critical architectural decisions for services built on Ruby on Rails and Python FastAPI, deployed via Terraform and guide the team on architectural choices. • Make critical technical and architectural calls within the timelines the team needs. • Drive proactive de-coupling of services and application of sound microservices patterns as ControlCheck scales. • Identify and resolve the hardest technical problems in the codebase — expert-level debugging across distributed systems and complex applications • Help elevate the whole team's technical ability and execution — the goal is doubling (or more) the team's collective output, not just personal 5–10x contributions • Lead cross-team dependency management and coordinate cross-discipline efforts with Product, QA, and adjacent engineering teams while maintaining productive relationships across the organization. • Communicate large systems and technical tradeoffs clearly to both engineering and non-technical stakeholders, including in roadmap and planning conversations • Influence at the Engineering Manager level — partner closely with your EM and fellow technical leads on team execution, hiring signal, and technical roadmap and provide technical guidance across the broader engineering team, not just direct collaborators. • Mentor senior engineers and serve as an escalation point for the team's most difficult technical challenges • Maintain a 'customer service' mentality toward the rest of the team — your job is to help make everyone else's work better

• Design and architect modern software solutions — from requirements analysis and architectural decisions through to production implementation • Take responsibility for scalable, maintainable and high-performance system designs based on modern technologies and cloud platforms • Participate in exciting client projects as the technical point of contact for architectural questions • Identify and incorporate AI-driven features or use cases into architectures where they make sense functionally and are economically viable • Design the integration of machine learning models, large language models (LLMs) or data-driven services into existing or new systems — depending on the project context • Provide technological advice to our clients on architecture and technology decisions • Ensure code quality and adherence to architecture standards through clean code, testing, reviews and best practices • Actively shape new technological topic areas — especially in the growing field of artificial intelligence