VP-Distinguished Engineer of Generative AI Engineering
About The Position
Slate Automotive is seeking a founding architect for its Generative AI capability as it builds an AI-native company. This deeply hands-on leadership role will design, build, and ship Generative AI systems for vehicle engineering, manufacturing, and customer service. The successful candidate will write code, make architectural decisions, lead by example, and build a lean team of GenAI engineers, MLOps engineers, and applied scientists while remaining actively involved in technical work. The role will establish Slate’s end-to-end GenAI platform, including its context and data layers, model serving, agent frameworks, and evaluation pipelines. It will deploy agentic systems across company functions, develop proprietary AI capabilities based on Slate’s decisions and knowledge, and bring AI into physical operations such as manufacturing, design tooling, and the supply chain. The position will also shape the engineering culture and standards for AI-first development.
Requirements
- 12 or more years of engineering experience.
- 3 or more years building and shipping production Generative AI systems, including LLM-based applications, agents, or RAG pipelines.
- 5 or more years in a senior technical leadership capacity.
- Deep hands-on experience with LLM APIs such as OpenAI, Anthropic, and Gemini; open-source model deployment; vector databases; agent orchestration frameworks such as LangChain or LlamaIndex; and prompt engineering at scale.
- Proven ability to take GenAI systems from prototype to production, including evaluation frameworks, guardrails, observability, and continuous improvement loops.
- Experience fine-tuning and training purpose-built models for domain-specific tasks.
- Ability to evaluate tradeoffs among hosted APIs, open-source models, and custom training in relation to cost, latency, and intellectual property.
- Grounding in modern data stacks such as Snowflake, Databricks, and dbt, and cloud infrastructure such as AWS, GCP, or Azure.
- Comfort reasoning about cost, latency, and data architecture as first-class constraints.
- Bachelor of Science degree required.
Nice To Haves
- Master’s or PhD in Computer Science, Machine Learning, or a related field.
Responsibilities
- Architect and ship the end-to-end Generative AI platform, including the context layer, data layer, model serving, agent frameworks, and evaluation pipelines, on a modern cloud foundation.
- Recruit and grow a high-performing team of GenAI engineers while remaining hands-on through coding, pull request reviews, architecture decisions, and shipping work alongside the team.
- Deploy GenAI agents across vehicle engineering, manufacturing, supply chain, software development, and go-to-market workflows.
- Build a proprietary context layer that captures agentic, human, robotic, and enterprise decisions, along with a unified data layer for training purpose-built models on Slate decisions.
- Partner with Vehicle Engineering, Manufacturing, and Quality teams to integrate AI into factory operations, design tooling, and the supply chain.
- Establish engineering culture, standards, and practices that attract AI talent and improve the quality of GenAI output.
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- Vacation
- 401(k)
- Potential eligibility to participate in an equity program
- Potential eligibility to participate in a discretionary annual incentive program
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What This Job Offers
Job Type
Full-time
Career Level
Executive
