Lead architecture and implementation of Auger’s data lake and AI platform, building scalable data ingestion, semantic intelligence (knowledge graphs, embeddings, RAG), real-time streaming, and MLOps. Drive system reliability, operational rigor, API-first designs, and mentor engineers while setting platform-wide architectural direction.
Build at Auger
Auger is the autonomous operating system for supply chains — the layer that finally allows disparate systems like ERP, WMS, and TMS to work together instead of against each other.
Most supply chain software surfaces problems and waits for a human to act. Auger solves them. Our AI detects disruptions, evaluates trade-offs, and executes decisions automatically — moving from signal to action in seconds, not weeks. We eliminate the Coordination Tax: the billions in capital and time lost when disconnected systems force the best people in the business to become the Human API between planning and execution.
At Auger, we design autonomy into our systems. We expect the same from our people.
That means:
- Clear ownership, not decision by consensus
- First principles over inherited patterns
- Shipping systems, not slide decks
- Fast feedback from reality, not opinions
If you want to build, ship, and iterate against reality, Auger is for you.
Auger was founded by Dave Clark and is backed by $150M from Oak HC/FT and Eclipse Capital. Our team works from Bellevue, WA and Dallas, TX.
About the Team & RoleAt Auger, we are reimagining how global supply chains operate by harnessing the power of data, AI, and next-generation technologies. Central to this vision is the design and evolution of a cutting-edge data lake and AI platform, the backbone of our real-time insights, intelligent applications, and advanced decision-making capabilities. As a Principal Engineer for the Auger Platform, you will bring deep expertise in the following:
What You'll Do
- Own end-to-end systems architecture across data pipelines, AI/ML platforms, semantic layers, and application interfaces — designing for modularity, scale, and durability from day one.
- Build and evolve the data integration layer: ingestion, normalization, and orchestration across structured and unstructured sources, using API-first design principles (REST, GraphQL, gRPC) and real-time streaming technologies like Kafka and Apache Pulsar.
- Architect the semantic intelligence layer: knowledge graphs, ontology design, vector embeddings, and RAG techniques that give Auger context-aware reasoning across the full enterprise data fabric.
- Design and operate scalable AI/ML platforms for training, deployment, and model lifecycle management — integrating LLMs, embeddings, and multimodal models into production applications via MLOps tooling (MLflow, SageMaker, Databricks).
- Drive AI into the application layer: partner with product and design to ship agentic, adaptive user experiences that surface intelligence at the moment operators need it.
- Set architectural direction across the platform: make layer boundaries, evolution strategies, and tradeoffs explicit — and document decisions the team can execute against with confidence.
- Raise the bar on operational rigor: fault tolerance, high availability, observability, and performance at enterprise scale are non-negotiable properties, not afterthoughts.
- Mentor engineers on system design, coding standards, and operational excellence — and hold a high bar on what ships.
What You Bring
- Bachelor or Master's degree in Computer Science, Engineering, or a related field.
- 10+ years of experience in systems architecture, software engineering, and platform development — with a proven track record building scalable data platforms or AI-driven systems at enterprise scale.
- Deep programming expertise in Python, Java, or C++, and hands-on experience building distributed systems in cloud-native environments (Azure, AWS, or GCP, including multi-cloud).
- Fluency in real-time data processing and analytics frameworks (Spark, Kafka, Flink) and big data technologies (Databricks, Snowflake, Hadoop).
- Advanced understanding of semantic modeling, knowledge graphs, and ontology design — including graph databases, graph embeddings, link prediction, and GNNs.
- Hands-on experience with AI/ML pipeline design and deployment, including frameworks such as TensorFlow, PyTorch, or equivalent, and familiarity with architectural patterns including microservices, event-driven architectures, and domain-driven design.
- Technical leadership through ambiguity: you set direction, communicate tradeoffs clearly to technical and non-technical partners, and write crisp architecture decisions when the stakes are high.
Auger considers all qualified applicants for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Additionally, our privacy policy is available at https://auger.com/privacy-notice/.
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