---
title: 'Principal Software Development Engineer at Auger'
canonical: 'https://feeny.ai/job/principal-software-development-engineer-auger-bellevue-tjspsayqd811'
type: 'job'
last_seen: '2026-10-14'
---

# Principal Software Development Engineer at Auger

- **Company:** Auger
- **Location:** Bellevue, WA
- **Compensation:** $280k–$330k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-03-26
- **Last confirmed live:** 2026-10-14
- **Apply:** https://jobs.gem.com/auger/am9icG9zdDqF9OtLq0iQ9-wa_O4b2WV2

## Job description

## About the Team

Every autonomous execution decision Auger makes starts with the AI Enablement Engineering team. This team transforms complex, disconnected customer data into a rich semantic backbone that gives our AI systems a deep understanding of each customer’s business. This team's work gives our AI the context it needs to reason, plan, and execute. This isn’t just a data engineering team. It's the team building the tools and the layer that gives Auger a competitive edge and enables delivery of measurable business outcomes for our customers.

## What You’ll Do

As a Principal Software Development Engineer, you bring a strong data engineering background. You will lead hands-on execution while raising the bar for how we build, validate, and operate data systems.

- Design and implement reusable, agentic AI frameworks across heterogeneous customer data sources so the team can rapidly discover schemas and semantics, generate ETL transformation logic in medallion style that hydrates the gold semantic layer, write performant SQL, and run efficient end-to-end data troubleshooting in a consistent, scalable way. Mentor the team on AI-native best practices.
- Own data engineering architectural designs and shape technical direction for the data team: standards for medallion-style lakehouse pipelines, boundaries between layers, evolution strategies, and data quality standards.
- Partner across product, science, and the data-tools platform to translate ambiguous needs into durable designs—aligning data models, semantics, and schema contracts with what customers experience in the product. Align business validation rules and data contracts with the Science team, and requirement-definition contracts with the Product team.
- Operating excellence: Practice operating excellence and test-driven engineering for data: define what “correct” means for critical datasets, and encode that in dev → test → prod paths. Institutionalize observability and reliability engineering for data: SLOs, monitoring, incident response, backfill/replay strategy, and elimination of recurring failure modes.
- Own the interface where data pipelines and ML pipelines meet. Turn data pipeline outputs into schema-bound datasets that feed machine learning. Turn ML results into reliable writes to the semantic layer. Define and enforce clear schemas and contracts to decouple fast-moving model logic from the system of record.

## What You Bring

- Degree in Computer Science or another data-intensive field, with principal-level experience. 10+ years in professional development, including 8+ years hands-on with SQL and Python and strong familiarity with at least one large-scale engine (e.g. Spark). 8+ years across data management (structured and semi-structured), modern warehouses/lakehouses, ETL/validation, and schema design in complex domains.
- Production ownership: Track record owning large-scale production data systems in distributed environments—on-call, incidents, and lasting reliability improvements (not just one-off fixes).
- Engineering discipline for data: Test-driven habits for transforms—unit/integration patterns, contract tests between layers, and data quality checks tied to business meaning. Experience defining standards for quality, observability, anomaly detection, or reliability and getting teams to adopt them.
- AI-native workflow: Comfortable with AI-assisted development for data work, with rigorous validation—you recognize when generated SQL or pipelines are wrong and know how to prove they’re right.
- Leadership & Communication: Technical leadership through ambiguity—set direction for frameworks and conventions, mentor others, communicate clearly both with customers and with internal technical and non-technical partners.
- Deep curiosity in ambiguous, high-impact problems; sound judgment under urgency; patience to fix root causes, not symptoms.
- A plus if you have prior experience in supply chain, planning, or fulfillment domains.

## About Auger

## Company Overview
- **One-liner**: Auger is building the world’s first autonomous operating system for supply chain operations, collapsing the gap between signal and execution with AI-powered automation.
- **Entity Type**: Private (Series A)
- **Headquarters**: Bellevue, Washington, USA
- **Founded**: 2024
- **Founders**: Dave Clark (Founder & CEO), Leigh Anne Clark (Co-Founder and President, Fashion and Beauty)

## Core Business
- **Primary industry/industries**: Supply Chain Technology, Enterprise AI, Logistics Software
- **Target customers**: B2B, Enterprise (large-scale supply chain operators, retailers, manufacturers, logistics providers)
- **Mission or purpose statement**: "To eliminate the Coordination Tax that traps enterprises in manual silos and fragmented systems. To make superhuman operations available to every enterprise ready to lead."

## Products & Services
- **The Autonomous Operating System**: A unified AI-powered platform that integrates with existing enterprise systems to provide real-time intelligence, cross-system synchronization, and autonomous execution of routine supply chain tasks (demand shifts, lead time management, capacity planning, scheduling). The system turns messy data into executable truth, allowing operators to move from firefighting to strategic work.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric – Total Funding**: $400M across three rounds (Seed, Series A, Series A extension)
- **Notable Investors/Partners**: Oak HC/FT (lead investor in initial $100M Series A)
- **Growth Signals**:
  - Headcount grew **223.9% YoY** (from ~26 to 129 employees)
  - LinkedIn follower count grew **74.5% YoY** (currently 12,855)
  - Active job postings: 17 (up 88.9% YoY)
  - Major talent pipeline from Amazon (26 hires), Microsoft (9), AWS (7), Meta (4)

## Competitive Advantages
- **Founder pedigree**: Led by Dave Clark, former CEO of Amazon’s worldwide consumer business — deep operational credibility at global scale.
- **"Living Ontology" approach**: Not layering AI on top of broken legacy systems, but building a unified data fabric across the entire enterprise.
- **Consumer-grade UX**: Makes complex supply chain tasks accessible through simple, intuitive interfaces (e.g., natural language queries for inventory insights).
- **Team composition**: 53% of employees in technical roles; includes a Chief AI and Agentic Scientist, Chief Supply Chain Scientist, and Chief AI Economist — rare depth of domain AI expertise.

## Strategic Focus
- **Autonomous execution**: Replacing the "speed of consensus" (manual coordination, meetings, spreadsheets) with real-time, automated reflexes.
- **Sustainability**: Positioning autonomous execution as the architecture for sustainable scaling — reducing excess inventory, expedited shipments, and waste.
- **Expanding beyond supply chain**: The company states it will expand "wherever coordination breaks down," suggesting a platform play across adjacent operational domains.

## Why Work Here
- **Culture highlights**: Described as a "pioneering venture" with a human-centered approach to solving broken supply chains. The team is composed of operators who "have lived the consequences" — late nights, impossible trade-offs — and are building to eliminate that pain for others.
- **Remote/hybrid/office policy**: In-office roles (e.g., Strategic BDR listed as "In-Office"). HQ in Bellevue, WA, with additional offices in Clyde Hill, WA and Bellevue, WA.
- **Notable perks or engineering culture**: Heavy investment in deep technical talent (AI, data science, supply chain science). Emphasis on moving from "firefighting to reinvention." Backed by top-tier VC with substantial runway ($400M total funding). Strong pipeline of ex-Amazon, Microsoft, and Meta engineers.

## Sources
1. [auger.com](https://auger.com/about/)
2. [linkedin.com](https://linkedin.com/company/augerinc)
3. [builtin.com](https://builtin.com/company/auger)
4. [cbinsights.com](https://www.cbinsights.com/company/auger)
5. [theorg.com](https://theorg.com/org/auger-1)

## Other roles at Auger

- [VP, Head of Finance](https://feeny.ai/job/vp-head-of-finance-auger-dallas-gyqeqqep0f62) — Dallas, TX
- [Software Development Engineer](https://feeny.ai/job/software-development-engineer-auger-bellevue-v5g9bd4tykz8) — Bellevue, WA
- [Deployment Strategist](https://feeny.ai/job/deployment-strategist-auger-dallas-c7j3rqsgv615) — Dallas, TX
- [Principal Software Development Engineer](https://feeny.ai/job/principal-software-development-engineer-auger-bellevue-rst59fsvcgwm) — Bellevue, WA
- [Principal Product Manager - Platform Experience](https://feeny.ai/job/principal-product-manager-platform-experience-auger-bellevue-xvsrrkh9azm3) — Bellevue, WA
- [Applied Scientist - Supply Chain](https://feeny.ai/job/applied-scientist-supply-chain-auger-bellevue-gw6nyzm5ktcm) — Bellevue, WA
- [Software Development Engineer - Front-End](https://feeny.ai/job/software-development-engineer-front-end-auger-bellevue-8gc0qdn8jnn8) — Bellevue, WA
- [Data Scientist - Supply Chain](https://feeny.ai/job/data-scientist-supply-chain-auger-bellevue-2gzs2y0xfes2) — Bellevue, WA
- [IT Operations Engineer](https://feeny.ai/job/it-operations-engineer-auger-dallas-8ffh6xd5ezmg) — Dallas, TX
- [Security Engineer](https://feeny.ai/job/security-engineer-auger-bellevue-2vn9hm25dpr5) — Bellevue, WA