Principal Software Development Engineer

Clear ownership, not decision by consensus

First principles over inherited patterns

Shipping systems, not slide decks

Fast feedback from reality, not opinions

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.

Bachelor or Master's degree in Computer Science, Engineering, or a related field.