Senior Python AI Engineer — Production LLM & Agent Systems

Limestone Digital

Central (LA)

On-site

USD 101,000 - 168,000

Full time

19 hours ago
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Job summary

Limestone is seeking a senior software engineer to build production-grade LLM and agent systems for a Dutch asset-manager client. The role emphasizes end-to-end ownership of Python services, strong SQL with Snowflake, and Azure DevOps CI/CD practices.

The project involves embedding an AI velocity pod within the client’s Azure tenant, delivering value streams one at a time, and working closely with client technologists in a regulated environment.

Qualifications

  • 5+ years of commercial software engineering experience, including production-grade LLM/agent systems.
  • Strong Python production practices: typing, tests, packaging, async, API clients, error handling.
  • SQL proficiency with a columnar warehouse (Snowflake preferred).
  • Experience with MCP connectors, evaluation harnesses, trace dashboards, and cost telemetry.

Responsibilities

  • Frame the value stream with the client team and map systems of record and Python tools.
  • Build the smallest useful data slice on real data in the client tenant with observable traces and human review.
  • Harden the architecture with security review, observability, fallbacks, and CI/CD in Azure DevOps.
  • Embed the harness and enable users, monitoring adoption and live failure patterns.
  • Deliver with Limestone within a single client value stream and coordinate with the core team.

Skills

Python
SQL
LLM/agent systems
Azure

Tools

Snowflake
Azure DevOps
Foundry
Cortex

Job description

Limestone is seeking a senior software engineer to build production-grade LLM and agent systems for a Dutch asset-manager client. The role emphasizes end-to-end ownership of Python services, strong SQL with Snowflake, and Azure DevOps CI/CD practices.

The project involves embedding an AI velocity pod within the client’s Azure tenant, delivering value streams one at a time, and working closely with client technologists in a regulated environment.

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