# Staff Backend Engineer at Doss

> Onsite · United States · Staff · Backend · open. Source: https://alderhq.app/jobs/ashby%3Adoss%3A769ddd26-b23c-4e0d-a2da-432565e25e0a (read 2026-11-05).

## Facts (observed)

- Company: [Doss](https://alderhq.app/companies/doss)
- Location text: San Francisco
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco")
- Posted: 2025-07-08 (485 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/doss/769ddd26-b23c-4e0d-a2da-432565e25e0a
- Skills listed (inferred): Ruby/Rails, PostgreSQL, Elasticsearch, Terraform, Snowflake

## Pay and sponsorship

- Posted pay: $230k–$260k per year (from the listing's pay field)
- Market band for similar posted roles (SF Bay Area, n 71): p25 $225k, median $245k, p75 $261k
- H-1B filings at this company for similar roles, FY26: 3, median offered wage $215k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

### About Doss

### DOSS is building an Operations Cloud for the real world.

A modern, AI-native platform for physical product businesses to manage the flow of goods, dollars, and data in real time, across:

Procurement

Inventory

Orders

Fulfillment

Finance

Built to replace spreadsheet chaos and rigid, consultant-heavy ERPs. Fast time-to-value, adaptable as the business evolves.

Through our Adaptive Resource Platform (ARP) and unified operational data model, teams deploy quickly, automate workflows, and make changes without months of re-implementation.

We recently raised a $55M Series B, co-led by Madrona and Premji Invest. Participation from Intuit Ventures, Theory Ventures, General Catalyst, Contrary Capital, and Pathlight VC.

DOSS is trusted by fast-growing operators to run critical operations with speed, control, and confidence.

### What You'll do

Design the core EAV data model & schema‑as‑code platform that powers every customer’s instance, balancing extreme flexibility with transactional integrity.

Build a Git‑style version‑control + migration engine capable of rolling forward/back complex schema and data changes on live production tenants in enterprise settings.

Engineer AI‑assisted tooling that uses foundation models to propose, validate, and apply new customer schemas and workflow definitions.

Scale our white‑labeled data warehouse (BigQuery/Snowflake‐like) for high‑volume, low‑latency analytics and automation workloads.

Create Terraform‑like declarative APIs & SDKs so ops teams can treat business processes as code while you ensure security, tenancy, and performance.

Deliver end‑to‑end observability & search across supply‑chain, finance, and ops data—surfacing business logic in plain language through AI‐native search.

Build Enterprise guard rails into a composable system to proactively detect anomalous behavior or risky emergent patterns

Mentor and shape engineering culture, partnering with product and design to turn unsexy back‑office pain into elegant, resilient systems loved by operators.

### What We're Looking For

### Experience

Expertise building large scale ETL on databases like Postgres, Elasticsearch, DuckDB, Memgraph (Graph DB), etc

Using cloud services to build + deploy reliable web applications

Working in abstractions to build complex graph-based architectures that scale

### Qualities

Team player: you bring positivity, openness, and curiosity to the team every day.

Growth mindset: everything is an opportunity to learn and improve yourself, the team, and the company.

Craftsmanship: you care about making something of quality.

Pragmatic: you make the right decision based on circumstance, not theory.

Low Ego: you work best in collaborative environments where everyone supports the team.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Adoss%3A769ddd26-b23c-4e0d-a2da-432565e25e0a and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.