AI Developer II

About Aurigo

Aurigo is an American technology company founded in 2003 with a mission to help public sector agencies and facility owners plan, deliver and maintain their capital projects and assets safely and efficiently. With more than $300 billion of capital programs under management, Aurigo’s award-winning software solutions are trusted by over 300 customers in transportation, water and utilities, healthcare, higher education, and government on over 40,000 projects across North America. We are a privately held corporation headquartered in Austin, Texas, USA, with software development and support centers in Canada and India. We are proud to be Great Place to Work Certified three times in a row. If you are ready to work for a fast-paced software company growing exponentially and interact with some of the brightest minds in the industry to solve real problems, we want to talk to you.

Description:

We are seeking a Senior AI Developer (GenAI specialization) to design, build, and operate production‑grade Generative AI systems that enable natural‑language interaction over large‑scale enterprise document ecosystems.

This is a builder and systems‑engineering role, not a research or analytics position. You will work from first principles to engineer robust, scalable, and observable GenAI platforms, owning critical components across the lifecycle—from document ingestion and retrieval to LLM orchestration, API serving, and cloud deployment.

You will collaborate closely with senior engineers and architects while taking clear ownership of execution‑level design and delivery for core GenAI systems.

Requirements:

Minimum 3 years plus experience in building GenAI.

Strong hands‑on experience building GenAI / LLM applications from scratch, beyond simple API consumption or demos.

Deep practical expertise in:Document chunking strategies, Metadata extraction, Multi‑format document pipelines (PDF, DOC, HTML, etc.), Context and memory management for conversational systems.

Vector databases in production: indexing, retrieval optimization, and performance tuning.

Advanced RAG techniques: hybrid retrieval, re‑ranking, and multi‑step retrieval.

Production LLM integration using AWS Bedrock, Azure OpenAI, or similar platforms.

Experience with evaluation frameworks for RAG systems and conversational AI.

Solid understanding of monitoring, reliability, and cost optimization for AI systems.

Competencies