About RivianRivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what's possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Role SummaryRivian Autonomy is building an Applied General AI team to make AI a dependable part of how hundreds of engineers develop, test, and ship software. We are seeking a Staff Software Engineer to own and evolve the agent platform behind that effort, spanning code generation and review, debugging, CI triage, operational support, and knowledge retrieval across our cloud, data, simulation, and vehicle-software ecosystem.
Autonomy operates one of Rivian's largest engineering data platforms, including petabyte-scale sensor data and ML training pipelines. This creates an unusually rich environment for agent systems: complex real-world workflows, valuable telemetry signals, and outcomes that can be objectively tested.
You will pair a production-grade agent platform with a rigorous evaluation loop so that every expansion of agent autonomy is supported by measured results on real Rivian work, not demos or anecdotes. Success means reducing the quality-adjusted effort required to complete important workflows while maintaining explicit security, reliability, software-quality, and developer-experience guardrails.
As an early member of the team, you will help define its technical direction, operating model, and future hiring. You will build on an existing in-house multi-agent system with real users and partners across all of Rivian Autonomy and beyond.
ResponsibilitiesAgent platform- Architect and build the core runtime for autonomous agents operating on Rivian systems, including orchestration, isolated execution, tool and skill frameworks, durable state and context management, model routing, policy enforcement, and end-to-end tracing.
- Establish an execution and permission model with isolated workspaces, short-lived task-scoped credentials, human-in-the-loop approval gates, network and data-access controls, and complete audit trails.
- Deliver capabilities across the engineering lifecycle, including code generation and review, debugging, test and CI failure attribution, documentation and knowledge retrieval, and operational triage, integrated with Slack, GitLab, Kubernetes, AWS, Databricks, and adjacent systems.
- Own the reliability of the platform and the lifecycle of long-running agent work, including recovery, cancellation, resource controls, and human escalation.
Evaluation and continuous improvement- Instrument agent workflows to capture traces, tests, diffs, review dispositions, task outcomes, and what engineers keep, modify, or reject. Build evaluation sets from representative Rivian engineering tasks and calibrate model-based grading against human judgment.
- Define repeatable, per-workflow success metrics; quantify run-to-run variance; and automatically detect regressions as models, prompts, context, and tools evolve.
- Design controlled rollouts that measure changes in engineering effort, cycle time, rework, quality, reliability, and developer experience. Measurements will evaluate tools and workflows, not individual engineer performance.
- Drive improvement through systematic experiments over prompts, context construction, tools, models, and inference budgets. Use the results to determine where agents earn greater autonomy and where they should be constrained.
Technical strategy and adoption- Define the technical strategy and roadmap for AI developer productivity across Autonomy, including build-versus-buy decisions, platform boundaries, security standards, and prioritization of the workflows with the greatest measurable impact.
- Work directly with engineers to identify high-friction workflows and understand where agents fail in practice. Turn those findings into improvements to context, tools, skills, interfaces, documentation, and enablement.
- Track credible advances in LLMs and agent systems and validate promising techniques on Rivian tasks before adopting them. Guide model tiers, reasoning depth, sampling, and verification strategies within explicit latency, reliability, and spend budgets.
- Lead architecture across organizational boundaries, communicate recommendations to engineering leadership, and mentor engineers building on the platform.
Qualifications- 6+ years of software engineering experience or equivalent demonstrated experience and impact, including substantial backend or distributed-systems work across cloud infrastructure, service design, storage, queuing, or secure execution.
- Staff-level technical leadership: you identify the problems worth solving, shape strategy across teams, make pragmatic tradeoffs, and drive ambiguous initiatives from evidence to production.
- Hands-on experience building and operating LLM applications, agent systems, or closely related developer infrastructure beyond prototypes, including tool use, orchestration, retrieval, context management, and production failure modes.
- Demonstrated rigor in evaluating ML, LLM, or other nondeterministic systems. You have designed metrics or experiments for a real product, understand statistical variance, and can defend or challenge whether a measured improvement is real.
- Strong understanding of the cost, latency, quality, and reliability tradeoffs that drive agent-system design.
- Strong programming skills in Python and experience with at least one additional relevant language such as Go, Rust, C++, or TypeScript.
- Strong communication and developer empathy, with a track record of building platforms or tools that engineers adopt and trust.
- Self-directed in ambiguous problem spaces and comfortable defining scope where no established playbook exists.
Bonus Points- Experience building evaluation harnesses, benchmark or task suites, or calibrated model-graded evaluations.
- Production experimentation experience, including A/B testing, causal inference, or offline-to-online metric correlation.
- Experience with MCP or other agent-interoperability protocols, plugin and skill frameworks, LLM gateways, or model-routing layers.
- Background in developer experience and tooling design for engineers.
- Experience with AWS, Kubernetes, GitLab-based CI/CD, and large
Pay DisclosureThe salary range for this role is $206,500-$258,100 for San Francisco Bay Area based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs.
We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian's 401(k) Plan and Employee Stock Purchase Program if you meet certain eligibility requirements. Full-time employee coverage is effective on their first day of employment. Part-time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com.
Equal OpportunityRivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.
Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at
Candidate Data Privacy and TechnologyRivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes ("Candidate Personal Data"). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law.
Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian's service providers, including providers of background checks, staffing services, and cloud services.
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How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Rivian uses iCIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role.
AI does not make hiring decisions: Qualified candidate applications are reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate.
Participation in AI profile matching is entirely voluntary. If you prefer that your profile not be used in this process, you can opt out at any time. Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system. Your current application remains active and will not be affected in any way.
Please note that we are currently not accepting applications from third party application services. 
