Software Engineer - Insights Platform

About Applied Intuition

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company creates the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition serves the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy.

Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.;
San Diego;
Ft. Walton Beach, Florida;
Ann Arbor, Michigan;
London;
Stuttgart;
Munich;
Stockholm;
Bangalore;
Seoul; and Tokyo.

The Insights platform is the data and analytics layer underlying Applied Intuition's physical AI development tooling suite. We own the full stack — from ingestion and query infrastructure to data discoverability, dataset management, and next‑generation agentic analytics. Our platform gives autonomy engineers complete visibility and control over the data their workflows produce: sensor logs, simulation runs, model evaluation results, KPIs, and more.

It gives users the flexibility to analyze and operationalize that data quickly, minimizing any technical barriers. We’re building the next‑generation Insights platform for physical AI — one that scales alongside the fleets, simulation environments, and end‑to‑end models that define where the industry is headed.

• Ingestion & Data Reliability – The entry point for all data on the platform. The correctness, freshness, and reliability of everything downstream depends on getting this right at scale across a diverse set of upstream sources.
• Query Critical Path – The infrastructure every single query in our product flows through. Latency, correctness, and stability here has a direct, visible impact on every user of the platform, every day.
• Dashboarding & Autonomy‑Native Visualization – The analytics surface that users actually see. Beyond standard BI, we build visualizations and integrations specific to physical AI: geographic views, log and simulation playback, and domain‑specific renderers that don't exist off the shelf.
• Agentic Analytics – The frontier of what Insights becomes. Building the architecture that lets an AI understand a user's intent, reason about the underlying data and physical AI concepts, and deliver answers, charts, and dashboards entirely through natural language.
• Data Discoverability & Governance – The connective tissue that lets users and agents understand what data exists, where it came from, and how to use it. Without this, scale becomes a liability rather than an asset.
• Dataset Lifecycle Management – The operational foundation that keeps the data lakehouse healthy and performant as data volumes grow by orders of magnitude.
• Data Wrangling & Transformation – The tools that give users agency over their own data – enabling custom preparation and ETL flows without ever leaving the product.

This is a high‑ownership role on a small team building the infrastructure that the entire autonomy development workflow depends on. You'll have end‑to‑end ownership of systems used daily by engineers at some of the most sophisticated autonomous vehicle programs in the world — at a stage where your architectural decisions will shape the platform for years to come.

• 3+ years of industry experience
• Experience building production data infrastructure, platform engineering, or distributed systems
• Experience with large‑scale data processing and query execution at production scale
• Strong backend engineering fundamentals: API design, service reliability, query optimization, distributed system trade‑offs, telemetry and monitoring
• Experience with data lakehouse architectures, table formats, or query federation is a strong plus
• Comfort operating across the stack – from storage and query engines to APIs and product‑facing tooling
• Familiarity with building for observability: metrics, alerting,…