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Staff AI Engineer, Enterprise Applied AI

Rivian · San Francisco, US

Job description

Rivian is seeking an entrepreneurial, hands-on senior individual contributor to build and scale our Enterprise Applied AI solutions driving impact across internal teams. As an Staff AI Engineer you will design, build, and operate production-grade systems at the forefront of generative AI, partnering with leaders across the company to unlock transformative business value. You will set technical direction, own complex domains, and raise the engineering bar through architectural leadership, operational excellence, and pragmatic innovation with language models and machine learning. You will work closely with Operations (Manufacturing, Supply Chain, Procurement, Quality), Product, Sales, Customer Service, Finance, HR, and other internal partners to align technical solutions to measurable enterprise outcomes. We are open to location for this role, but relocation to a center of gravity office would be required. This role will report to our Principal AI Engineer.

  • Lead the technical design and hands-on development of prioritized AI applications, services, and platforms leveraging state-of-the-art LLM app stacks, retrieval-augmented generation, evaluation frameworks, and scalable serving.

  • Define long-term architecture and engineering standards for Applied AI systems to maximize reuse, reliability, and impact across multiple product areas.

  • Partner with business sponsors to translate high-value opportunities into roadmaps and shipped products with clear success metrics and measurable outcomes.

  • Build a holistic view of AI investments by collaborating with adjacent engineering groups implementing AI in their domains, aligning patterns, reusing components, and avoiding duplication.

  • Drive continuous improvement in AI methodologies and best practices; evaluate emerging capabilities and land them as secure, production-grade systems.

  • Collaborate with Legal, Compliance, Risk, Audit, and Security to embed robust governance, privacy, security, safety, and reporting practices across the AI lifecycle.

  • Champion AI literacy, enablement, and adoption through demos, guidance, and technical leadership across the org.

  • Mentor engineers across levels; lead design reviews; improve code quality, reliability, observability, and cost/performance of AI workloads.

  • Establish rigorous evaluation, guardrails, and monitoring practices; instrument offline and online metrics to ensure quality, safety, and SLOs.

  • Optimize latency, throughput, and cost at scale; guide make/buy decisions and vendor integrations where appropriate.

  • BS/MS/PhD in Computer Science or a related field, or equivalent experience.

  • 8+ years in software engineering, with a proven track record delivering complex, production-ready systems in enterprise environments.

  • Deep technical knowledge in AI/ML, with hands-on experience building and deploying solutions using language models, retrieval/grounding, embeddings/vector search, and evaluation.

  • Demonstrated ability to translate ambiguous business problems into robust AI products with measurable business impact.

  • Experience defining and evolving architectures, standards, and platforms that create leverage across multiple teams.

  • Strong familiarity with security, privacy, compliance, safety, and auditability for enterprise AI systems.

  • Excellence in communication and stakeholder management; able to influence and align across diverse teams.

  • Proven curiosity and mental agility to learn and apply new technologies through hands-on development and continuous learning.

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