Staff Software Engineer - Vehicle Data Services

Rivian and Volkswagen Group Technologies•Palo Alto, CA

6d•$167,400 - $209,300

About The Position

The Vehicle Data Services team is seeking passionate and skilled Staff Software Engineers to lead and support our Cloud Data Platform to build massively scalable and robust Data Services that deal with the ingress and egress of data to and from our Backend Applications. These newly created Software Engineer opening will support High throughput telemetry acquisition systems, handling streaming and batch data, data model registry and fleet orchestration for push updates. These Engineers will help build the future of how Cloud & Mobile services will operate and communicate with vehicles and other Cloud services. This team will create the electric architecture and software for next generation Software Defined Vehicles (SDVs). This new R | V Tech Employee will thrive in leading design, developing, and maintaining high-performance, low-latency, robust, scalable, and reliable distributed systems. This position will play a pivotal role in shaping the backbone of R | V Tech’s technology infrastructure, collaborating with cross-functional teams, and tackling complex technical challenges.

Requirements

Strong foundation in Software Engineering principles and Distributed systems design
Strong understanding of application authentication like OIDC and authorization models based on oauth. Building In skillsets, knowledge of ORY.sh, Okta or similar platform to implement permission management or user entitlements in services is highly preferred.
Proficiency in Go (GoLang) Programming, and Python, with demonstrated experience building production-grade applications.
Good understanding with multi-tier secure and scalable web patterns using REST & WSS
Experience with cloud platforms, preferably AWS, and familiarity with cloud-native patterns
Expertise in event-driven architecture and working with message brokers such as Kafka, Druid, and/or Pinot
Knowledge of Redis for caching, session storage, or distributed data structures
Understanding of data stores such as Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon DocumentDB, and/or MongoDB is preferable
Solid understanding of systems debugging, production, and monitoring tools such as Datadog and Amazon CloudWatch
Experience with unit testing, system testing, and performance testing
Experience building cost effective and efficient designs in your technology choices
Strong knowledge of Git for version control and collaboration
Ability to self-manage and drive projects to completion while working independently
Familiarity with CI/CD tools like Jenkins and GitLab CI/CD is also preferred.
Familiarity with communications protocols like Protobuf & GRPC is highly preferred.
Knowledge of containerization and orchestration tools such as Docker and Kubernetes.
Familiarity with Cloud infrastructure provisioning tools like Terraform, Terragrunt, Crossplane, ArgoCD
Familiarity Agentic frameworks and protocols such as MCP, ACP, etc is a real plus
Familiarity with AI First tools such as Cursor, Glean, etc
Masters in Computer Science, Engineering, or a related field is strongly preferred, but not required.

Responsibilities

Experience with technical team leadership for a team of mid-level & Senior engineers across multiple locales
Collaborate with cross-functional teams to understand system requirements and translate them into scalable technical solutions
Actively participate in long term strategic roadmap across Data Platform initiatives
Design, develop, and deploy distributed & API-based backend applications and microservices for R | V Tech's Vehicle Data Services Team with a focus on scalability, reliability, and performance.
Work with event-driven architectures, leveraging technologies like Kafka, Druid, Pinot and Redis to build efficient and fault-tolerant systems.
Write high-quality, maintainable code and ensure robust test coverage.
Implement, monitor, and debug applications, ensuring high availability and low latency.
Develop, deploy, and maintain solutions on cloud platforms, particularly AWS.
Manage and optimize message brokers and implement streaming and queuing solutions as required.
Proactively identify and address performance bottlenecks, scalability challenges, and production issues.
Participate in an on-call rotation, addressing production issues during off-hours as necessary.
Maintain comprehensive documentation for systems, processes, and tools.
Continuously improve CI/CD pipelines, monitoring, and alerting systems.