AI Solutions Specialist

AI Solutions Specialist

Archetype AI is developing the world's first AI platform to bring AI into the real world. Formed by an exceptionally high-caliber team from Google, Archetype AI is building a foundation model for the physical world, a real-time multimodal LLM for real life, transforming real-world data into valuable insights and knowledge that people will be able to interact with naturally. It will help people in their real lives, not just online, because it understands the real-time physical environment and everything that happens in it. Supported by deep tech venture fundsin Silicon Valley, Archetype AI is currently at the Series A stage and is progressing rapidly to develop technology for their next stage. This presents a unique and once-in-a-lifetime opportunity to be part of an exciting AI team at the beginning of their journey, located in the heart of Silicon Valley. Our team is headquartered in San Mateo, California, with team members throughout the US and Europe.

About the Role

Archetype AI is seeking an AI Solutions Specialist to join our high-velocity Go-To-Market (GTM) Sales team, reporting to the Head of Solutions Architecture. We're a fast-growing startup building Newton, our multi-sensor data fusion AI platform, and this role is all about rapidly turning customer ideas into working solutions. In this role, you will help validate customer use cases and shape the solutions they need by combining prompt engineering with AI/ML data workflows. You'll move quickly from reviewing incoming customer assets to designing prompts, preparing data, and running targeted evaluations. Working closely with Solutions Engineers and Sales Representatives, you'll help ensure customers quickly see relevant, high-impact results from their data. This is a hands-on, internally focused role in a fast-paced environment that rewards ownership, initiative, and a strong can-do mindset.

Skills & Qualifications

• Data Preparation, Prompt Engineering & Fine-Tuning Support
• Review and assess incoming customer assets (video, sensor streams data, use cases, requirements) for feasibility with Newton.
• Prepare datasets in Python for evaluation and fine-tuning, including ingestion, cleaning, structuring, and steps such as imputation, filtering, normalization, or other basic signal processing for model readiness.
• Support labeling and annotation workflows from dataset creation through evaluation.
• Use signal visualization and basic statistical analysis to assess and validate data preparation steps.
• Collaborate with engineering to investigate unexpected model performance and identify opportunities for improvement, noting that data preparation is often iterative (data prep testing refine prep repeat).
• Design, test, and refine prompts — including natural language and multimodal examples (e.g., n-shot examples in the Machine State Lens) — for Newton's lenses (physical agents) based on specific customer needs.
• Configure and adjust lens parameters to maximize performance on quick evaluations and proof-of-concept runs.
• Maintain a library of reusable prompt templates and configuration presets for common scenarios.
• Internal-Facing GTM Support
• Work closely with Solutions Architects, Solutions Engineers, and Sales Representatives to support the GTM team.
• Support Solutions throughout the entire customer engagement lifecycle — from top-of-funnel discovery through solution development, deployment, and follow-on expansion.
• Summarize evaluation findings for the Solutions teams, enabling faster follow-up with customers.
• Occasionally support demos or training sessions on prompt building and evaluation best practices.
• Take ownership of assigned evaluation projects, driving them from raw data to testable results without waiting for step-by-step direction.

Required Qualifications

• 4+ years as an AI/ML data analyst, or related technical role focused on AI/ML data preparation, analysis, and evaluation.
• Proven experience running both prompt engineering and fine-tuning workflows in production or prototyping environments.
• Hands-on work with raw time-series sensor data and/or video, including preparation, structuring, and formatting for AI/ML models.
• Experience executing iterative data preprocessing cycles (e.g., imputation, filtering, normalization): make targeted changes, re-run evaluations, inspect metrics/plots, compare against baselines, and retain improvements.
• Background in end-to-end dataset labeling and annotation workflows, from raw data through evaluation.
• Collaboration with engineering teams to diagnose model performance using time-series visualizations, embedding visualizations, and other diagnostic outputs.
• Proficiency in Python for data cleaning, API calls, and dataset preparation.
• Hands-on experience labeling and annotating data for model training, including preparing datasets for evaluation and fine-tuning (experience with tools such as Encord is a plus).
• Ability to structure and preprocess raw time-series sensor data and video for AI/ML workflows, including use of signal visualization and basic statistical analysis for validation.
• Familiarity with iterative data preprocessing loops (trial, assess, refine).
• Experience working with Jupyter Notebooks or similar.
• Experience generating customer-ready reports that present analysis results in a repeatable, consistent format.

Soft Skills & Attributes

• Startup-ready mindset with the ability to thrive in high-velocity, high-ambiguity environments.
• Self-starter with strong organizational skills and a bias for action.
• Comfortable working independently but collaborative in cross-functional projects.
• Clear communicator who can translate technical results into actionable insights for non-technical teams.