• Design, build, and support high‑performance APIs and microservices for vehicle history, VIN intelligence, and transaction systems. • Develop and scale Java/Spring Boot services in a modern AWS cloud‑native environment. • Architect event‑driven systems using Kafka, SQS, or similar technologies to enable asynchronous processing and data pipelines. • Contribute to platform‑wide decisions around architecture, scalability, resiliency, and security. • Implement and continuously improve CI/CD pipelines, automated testing strategies, and observability practices. • Participate in full SDLC ownership: design → build → deploy → operate (“you build it, you own it”). • Collaborate closely with product, data, and partner teams to deliver mission‑critical integrations. • Mentor engineers and help cultivate a high‑performing, collaborative engineering culture.

• Provide subject matter expertise to support proposal development, ensuring logistics approaches, methodologies, and solutions meet customer requirements. • Partner with capture, pricing, and proposal teams to develop logistics concepts of operations (CONOPS), staffing models, workflows, and technical volumes. • Review requirements related to supply chain, warehousing, inventory, transportation, and distribution to ensure compliance and alignment with customer expectations. • Craft clear, compelling technical narratives describing logistics capabilities, processes, technologies, and performance metrics. • Advise on feasible, cost effective logistics solutions to strengthen win themes and differentiators. • Support risk identification and mitigation strategy development for proposal submissions involving supply chain or transportation functions. • Provide recommendations on leveraging systems and industry best practices in proposal responses. • Engage on an as needed basis to answer technical questions, refine solution elements, and ensure the final product reflects sound logistics expertise.

• Develop world-class GPU-accelerated AI inference serving software • Contribute to feature development and drive broad customer adoption • Drive the convergence of the Triton Inference Server and NVIDIA Dynamo stacks to establish a unified, high-performance inference platform • Ensure feature parity and effectively serve both Large Language Model (LLM) and non-LLM workloads • Build robust software designed to be deployed in production server or cloud environments • Optimize and balance prediction throughput and latency • Develop and adopt the next generation of inference technologies

• Design, build, maintain and extend products, features, and functionality that solve real customer problems • Partner with Product, Design, and Engineering to discover and validate customer needs and technical approaches • Develop and extend integrations with onboard hardware devices such as headsign controllers, passenger counters, and fareboxes • Build and improve cloud-native backend services that manage device configuration, process telemetry data, and provide observability into fleet-wide device health • Implement and maintain robust mechanisms for over-the-air software deployment, configuration updates, and remote device management • Design testing strategies that account for the realities of hardware-in-the-loop systems including integration testing, simulated environments, and production monitoring • Maintain and improve our physical hardware lab if local to San Francisco, else contribute to solutions for remote development, testing, and debugging needs • Consistently deliver incremental value by anticipating dependencies, breaking down work, and regularly demoing progress • Communicate technical trade-offs, present system design proposals clearly, and document architectural decisions • Uplevel teammates through code reviews, pairing, and strong collaboration • Take ownership of your code and product domain, engaging in retrospectives and continuously improving how the team works