Senior Software Engineer - Cloud Platform

Latitude AI ( lat.ai ) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone. When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif. Meet the team: Latitude Cloud Platform engineers create reusable architecture via infrastructure as code for Latitude teams to leverage as common shared components and educate Latitude teams on how to architect their solutions for scale, security, and reviewed changes through automation. This includes ownership of the workload ecosystem on Kubernetes running on public and hybrid cloud environments. The Cloud Platform team interacts with engineering teams including ingest/data processing, mapping, labeling, triage, machine learning (detection, prediction, tracking), motion planning/control, offline simulation, and release/deployment teams to unify development practices and scalable efficiency of cloud/cloud native technologies. What you’ll do: Architect and scale a multi-tenant, hybrid-cloud Kubernetes platform to ensure seamless workload portability across public and internal environments Develop custom Kubernetes operators and self-service abstractions to simplify complex infrastructure management for autonomous vehicle engineering teams Optimize high-performance distributed workloads by architecting specialized compute environments for ML and simulation on heterogeneous hardware Standardize end-to-end GitOps workflows and CI/CD pipelines to automate security, networking, and observability across the infrastructure lifecycle Provide technical leadership and architectural guidance to ensure engineering teams build resilient, cost-effective services aligned with cloud-native best practices Manage the lifecycle of critical platform components like service mesh and networking while proactively resolving systemic bottlenecks in hybrid cloud environments What you'll need to succeed: Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD) Hands on development in Python, Go, or Java to create production level services that incorporate CI/CD Experience in using infrastructure as code to automate the creation of cloud resources. E.g. Terraform, CloudFormation, or others Strong experience with architecting/deploying scalable services and workloads in the cloud (AWS, GCP) and/or cloud native environments Strong experience with deployment management/scheduling/high availability/failure modes for distributed applications and compute workloads running on CPUs and GPUs Understand engineering design limitations and provide guidance for teams to scale their deployments in the cloud so that they can achieve desired performance within budget Experience creating reusable deployment patterns for teams to adopt, that incorporate networking, security, monitoring, logging, alerting, continuous integration and deployments Understanding of API specification languages (e.g. Open API/gRPC) and the ability to create reusable code via code generation, templates, and other rapid development techniques for teams to consume Leverage and modify open source tools to meet unique requirements for internal teams, including but not limited to Kubernetes, Prometheus, FluentD, Istio, Envoy, CoreDNS ... (truncated, view full listing at source)