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Sr. AI Engineer, Product Development

Rivian Tustin, CA

Tustin, CA

Today

Full time Agentic Ai Ai Agent Artificial Intelligence

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Job Description

Rivian is hiring a Sr. AI Engineer for its Product Development AI and Data Science team in Tustin, CA (onsite). The role focuses on building agentic AI capabilities and AI-ready data foundations, then applying evaluation frameworks to automate engineering workflows for software-defined hardware.

What You’ll Do

Partner with senior technical staff to design and orchestrate agentic AI workflows and LLM-powered systems that automate complex engineering activities, including documentation auditing, requirement generation, and technical knowledge retrieval.
Build, validate, and maintain ETL pipelines and supporting data structures, including knowledge graphs and vector databases, to deliver high-fidelity context to AI applications across siloed engineering systems.
Run rapid technical trials to assess emerging AI approaches, moving efforts from early concepts to functional prototypes to determine which methods best reduce engineering labor.
Convert early prototypes into robust, highly performant, scalable enterprise systems.
Define and monitor quantitative performance requirements, including accuracy, grounding, latency, and cost, aligned with safety and reliability expectations for vehicle engineering.
Collaborate across teams to identify manual engineering workflows and implement AI-driven automations that improve product development efficiency and productivity.

Required Qualifications

Bachelor’s, master’s, or PhD in a quantitative field (e.g., Computer Science, Electrical Engineering, Mechanical Engineering, Materials Science, Physics, Mathematics, or a related quantitative discipline).
Ideally 4 to 6+ years of experience building production data pipelines and developing AI/ML solutions, with LLM-based application experience preferred.
Experience in repository context engineering, AI-native IDEs and terminals, agentic loop optimization, and AI coding quality with technical debt mitigation.
Hands-on or deep academic knowledge of LLM orchestration and application concepts, including RAG (Retrieval-Augmented Generation), agentic frameworks, context engineering, grounding, evaluation, and cost and latency optimization.
Deep understanding of failure modes in AI systems versus traditional software, including statistical validation test design, tolerance thresholds, and tracking output distributions.
Demonstrated experience with Git, eval-driven CI/CD pipelines, probabilistic validation of AI systems, deployment, and end-to-end system ownership for production environments.
Experience with high-throughput storage systems, containerized harness orchestration, and security or sandbox environments.
Ability to extract, clean, and structure data from technical documents, requirements, or engineering specifications.
Prior experience in physical engineering systems (Hardware, IoT, or Telemetry).
Strong problem-solving skills with an emphasis on product development.
Excellent written and verbal communication skills for coordinating across teams and leading cross-functional efforts.
A drive to learn and master new technologies and techniques.

Technologies

LLM, RAG (Retrieval-Augmented Generation)
ETL
Knowledge graphs, vector databases
Git, CI/CD
Containerized harness orchestration
Neo4j, Pinecone
Spark, Databricks
GCP, DBT

Location and Experience

Location: Tustin, CA (onsite)

Minimum experience: 4 years

Nice to Have

Exposure to graph technologies (such as Neo4j or knowledge graphs) or vector databases (such as Pinecone).
Knowledge of advanced statistical techniques (for example, regression, distribution properties, and appropriate use of statistical tests) and experience applying them.
Knowledge of a range of machine learning techniques (such as clustering, tree-based methods, and deep learning) and understanding tradeoffs in real-world settings.
Experience building user-facing applications.
Experience with distributed data or computing tools, such as Spark, Databricks, and GCP.
Experience with DBT.
Interest in electric vehicles, renewable energy, and sustainable transportation.

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