> Markdown version of [/jobs/ext/2702326-ai-data-engineer](https://www.wearedevelopers.com/jobs/ext/2702326-ai-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI Data Engineer

- **Company:** AI Enabled Solutions LLC
- **Location:** Hartford, CT, United States
- **Experience:** Expert
- **Salary:** $117,200.0 - $175,800.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Extract Transform Load (ETL), Data Systems, Database Queries, Data Processing, Snowflake, Data Layers
- **Published:** September 4, 2026
- **Apply:** https://www.themuse.com/jobs/thehartford/sr-ai-data-engineer-8e40aa

## About the Role

* Working experience with ThoughtSpot, Snowflake, semantic data layers, and AI for analytics or agentic data solutions
 * 5-7 years of data analysis, manipulation and development
 * 1-3 years of experience in the insurance or investment industry
 * Strong SQL skills
 * Property and Causality Domain expertise preferred
 * Ability to design, implement, and oversee ETL processes
 * Familiarity with emerging data centric technologies
 * Ability to choose and effectively utilize data wrangling technologies, This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday). Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

## Description

You will serve as a hands-on builder and thought partner, helping develop analytic-ready data assets, governed semantic layers, AI prompts and context, and interactive analytics experiences that enable actuaries to identify opportunities, diagnose root causes, and deliver recommendations with greater speed, consistency, and confidence.


## Related Videos

- [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works)
- [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers)
- [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team)
- [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean)
- [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering)
- [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it)

## Related Articles

- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)
- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)
- [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)