Careers · Founding Engineers
Build the interpretation layer for business questions.
We are a small team with deep experience in business intelligence, relational engines, and metadata systems. We are building an AI analyst that shows how it interpreted a question before execution and exposes the evidence behind the answer.
What we're building
The AI analyst for business teams.
Spotonix interprets a question using available warehouse structure, supported semantic-model metadata, team-supplied definitions, and reusable analysis patterns. It represents the selected segment, calculation, filters, grain, and comparison in a visible analytical plan. When a missing business choice materially changes the path, the workflow can ask a person instead of silently choosing.
The engineering problem spans context ingestion, plan representation, generation, semantic checks, warehouse execution, and answer evidence. A visible plan is a review surface—not a correctness guarantee—so the product must also expose logic or SQL, sources, human interventions, and supporting artifacts. Making that path inspectable is the durable systems work we are hiring for.
Who we're looking for
Founding backend engineers — two roles.
We're at an exciting, early stage and hiring two founding engineering roles. Deep expertise in one is what we're after — bring it, and we'll teach you the rest.
01
Query & Analysis Systems
You will work on relational algebra, analytical planning, generation, semantic checks, and execution across warehouses. The challenge is to carry the material choices represented in a visible plan into generated logic and expose enough evidence for a person to inspect the result. Experience with a database engine, MDX or BI engine, or query optimizer is ideal.
02
Context & Metadata Systems
You will build the Context Graph: ingesting warehouse schema, supported semantic-model structure, team-supplied business definitions, and reusable analytical artifacts while preserving their origin. Experience with a data catalog, metadata platform, ETL system, or knowledge graph shines here.
Why build here
A career that compounds.
- Play a pivotal role in shaping the product and the company.
- Bleeding-edge tech combining generative AI, semantic processing, and analytics.
- Exceptional autonomy and accelerated career growth.
- A fast-paced, zero-to-one, first-generation product environment.
- No bureaucracy, no hierarchy — just lines of collaboration.
- Build alongside industry pacesetters who have done it before.
What we look for
Must-haves
- 3–8 years working in large, production-grade Python projects.
- Strong data structures, algorithms, design, and coding skills.
- Experience in a fast-paced startup / small team with 2–4 week release cycles.
- Comfortable writing production-quality modern Python.
Strong pluses
- ML stack: PyTorch, NumPy, Pandas.
- LLM toolchain: any modern stack.
- 2–4 years building a data platform (DB engine, data catalog, ETL engine, JDBC driver, MDX/BI engine).
Who you'll build with
Founders who've built this before.
Let's transform business intelligence together.
Send us a note — tell us which area is your strength and point us to something you've built. We look forward to deep technical conversations.
Questions? [email protected] · SF or remote (US) · Pier 5, Suite 101, San Francisco