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# Software Engineer

- **Company:** Velastegui Ventures LLC
- **Location:** United States
- **Experience:** Expert
- **Salary:** $210,000.0 - $250,000.0
- **Contract:** Temporary contract
- **Skills:** Amazon Web Services, Distributed Systems, Python (Programming Language), PostgreSQL, RabbitMQ, Message Oriented Middleware, Search Technologies, Data Streaming, AI Infrastructure, Retrieval-Augmented Generation, Large Language Models, Change Data Capture, Backend, Event Driven Architecture, AI Platforms, Kubernetes, Apache Kafka, Machine Learning Operations, Amazon Simple Queue Service (SQS), Terraform, Docker
- **Published:** September 30, 2026
- **Apply:** https://www.thejobnetwork.com/job/06daff89-098d-4c53-a14c-94cddd3af69d/principal-software-engineer

## About the Role

5+ years building and operating production backend systems, with meaningful ownership of distributed architecture.

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 - Strong proficiency in at least one of Go, Rust, or Python, and comfort working across a polyglot codebase.

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 - Solid grounding in distributed systems: asynchronous messaging, event-driven design, and the failure modes that come with them. Direct experience with a streaming or queue technology (Kafka, SQS, RabbitMQ, or similar) and the concepts

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behind Change Data Capture.

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 - Working knowledge of PostgreSQL and at least one non-relational store (vector, document, or graph).

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 - Fluency with AWS (or equivalent), containers (Docker/Kubernetes), and infrastructure-as-code (Terraform or similar).

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 - Real interest in - ideally hands-on experience with - applied AI/ML systems: embeddings, vector search, RAG, or LLM serving. This is an AI infrastructure role; curiosity here isn't optional.

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 - Communication skills to work directly with customers, compliance stakeholders, and product.

## Description

We build enterprise AI infrastructure that lets regulated organizations query their unstructured and structured data in natural language. Our platform combines retrieval-augmented generation, federated search, and self-hosted model inference to deliver citation-backed, auditable answers - deployed inside the customer's own cloud boundary. We're growing the engineering team to scale this platform through its first enterprise deployments and into a multi-tenant product.