10 hours ago
Base Salary
$207k - $258k/yr
Responsibilities
- Architect and build the production runtime for autonomous agents, including orchestration, isolated execution, tools and skills, durable state and context, model routing, policy enforcement, and end-to-end tracing.
- Establish secure execution and permission controls using isolated workspaces, task-scoped credentials, approval gates, network and data-access controls, and audit trails.
- Deliver agent capabilities for code generation and review, debugging, CI failure attribution, knowledge retrieval, documentation, and operational triage across Rivian systems.
- Own platform reliability and long-running agent lifecycle management, including recovery, cancellation, resource controls, and human escalation.
- Instrument workflows and create evaluation sets, metrics, model-based grading, regression detection, and controlled experiments based on representative engineering tasks.
- Define the technical strategy and roadmap for AI developer productivity, including platform boundaries, security standards, build-versus-buy decisions, and workflow prioritization.
- Work with engineers to identify workflow friction, improve agent context, tools, skills, interfaces, documentation, and enablement, and guide model and verification strategies within cost and latency budgets.
- Lead architecture across organizational boundaries, communicate recommendations to engineering leadership, and mentor engineers building on the platform.
Requirements
- 6+ years of software engineering experience or equivalent demonstrated experience and impact, including substantial backend or distributed-systems work in cloud infrastructure, service design, storage, queuing, or secure execution.
- Staff-level technical leadership with the ability to shape strategy, make pragmatic tradeoffs, and drive ambiguous initiatives from evidence to production.
- Hands-on production experience building and operating LLM applications, agent systems, or related developer infrastructure involving tool use, orchestration, retrieval, and context management.
- Experience rigorously evaluating ML, LLM, or other nondeterministic systems through metrics, experiments, variance analysis, or measurement validation.
- Strong understanding of cost, latency, quality, and reliability tradeoffs in agent-system design.
- Strong programming skills in Python and at least one additional relevant language such as Go, Rust, C++, or TypeScript.
- Strong communication and developer empathy, with experience building platforms or tools that engineers adopt and trust.
- Preferred experience includes evaluation harnesses, benchmark or task suites, calibrated model-graded evaluations, A/B testing, causal inference, offline-to-online metric correlation, MCP or other agent-interoperability protocols, plugin and skill frameworks, LLM gateways, model-routing layers, developer experience tooling, AWS, Kubernetes, GitLab-based CI/CD, and large-scale engineering data systems.
Benefits
- Comprehensive benefits are available to full-time and part-time employees, eligible spouses or domestic partners, and children up to age 26.
- Benefits include paid vacation, paid sick leave, life insurance, medical insurance, dental insurance, vision insurance, short-term disability insurance, and long-term disability insurance.
- Eligible employees may participate in Rivian’s 401(k) Plan and Employee Stock Purchase Program.
- Full-time employee coverage begins on the first day of employment; part-time coverage begins on the first day of the month following 90 days of employment.
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About Rivian
Doing something different is never easy. It requires courage, optimism and grit. Core to our mission is building a team of adventurous individuals determined to make a positive impact on the world. This means challenging ourselves constantly. Stretching beyond the bounds of conventional thinking. Reframing old problems. Seeking new solutions. And operating comfortably in a space of uncertainty. While our backgrounds are diverse, our team shares a love of the outdoors and a desire to protect it for future generations. Do you like doing the impossible? We’d love to hear from you.