Responsibilities

Develop and maintain high-volume streaming services that process real-time data from vehicles, cloud systems, and operations.
Create and manage Apache Flink applications and event-driven microservices using Kafka or Redpanda.
Construct streaming infrastructure that enables analytics, AI, and machine learning workloads as well as live operational decisions.
Design event-driven systems focused on high throughput, low latency, fault tolerance, and ease of operations.
Write production-ready streaming applications in Java, Scala, Python, or Go using industry-standard software practices.
Contribute to scalable streaming designs including topic structure, partitioning, checkpointing, savepoints, dead letter queues, replay methods, and recovery from failures.
Improve application performance by tuning for latency, throughput, resource efficiency, and cost-effectiveness.
Build reusable platform tools, SDKs, libraries, and self-service features to boost developer efficiency across teams.
Support deployment and operations using Kubernetes, Docker, CI/CD pipelines, and Infrastructure as Code.
Implement observability through metrics, logs, distributed tracing, dashboards, and proactive alerts.
Monitor and resolve issues in production systems using consumer lag, checkpoint status, logs, metrics, and dashboards.
Collaborate with platform, data, ML, analytics, and product teams to deliver full-stack real-time data solutions.
Develop pipelines that power AI/ML platforms, online feature computation, retrieval-augmented generation (RAG), and smart applications.
Participate in on-call support, incident response, root cause analysis, and ongoing improvements to system reliability.
Use AI-powered development tools to enhance code quality, testing, debugging, documentation, and engineering productivity while upholding strong engineering standards.

Compensation

Competitive base salary, annual performance bonus (discretionary), and eligibility for Restricted Stock Units (RSUs) subject to board approval and vesting terms.

Work Arrangement

On-site — Palo Alto, California

AI-Driven Engineering

AI is reshaping software development and operations. Engineers on this team are expected to actively use AI-assisted tools to speed up coding, testing, debugging, documentation, and system design, while upholding rigorous standards for code quality, security, and engineering integrity.

What Success Looks Like

Successfully delivers robust, scalable, and maintainable streaming systems that support critical analytics, operational, and AI workloads. Takes increasing ownership of production environments by improving reliability, performance, and developer experience. Designs solutions that balance speed, efficiency, resilience, and simplicity. Works cross-functionally with infrastructure, data, AI, and product teams to deliver high-impact results. Applies AI-enhanced development methods to increase velocity without compromising engineering quality. Builds reusable components that empower teams to develop event-driven and AI-powered applications efficiently. Stays current with emerging technologies and contributes innovative ideas to advance the real-time data platform and AI capabilities.

Other

Engineers are expected to thoughtfully use AI-assisted development tools to improve software design, implementation, testing, debugging, documentation, and operational excellence while maintaining high standards for code quality, security, and engineering judgment.
External candidates should apply through the company careers site.
Current employees must apply via the internal job board.
Candidates needing accommodations due to disability should email candidateaccommodations@rivian.com.
Benefits and compensation offerings vary by country.
Consent to receive SMS messages is not a requirement for employment consideration.

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