Remote Embedded AI Engineer for Finance & Analytics

Gigapower; Dallas (TX); On-site; USD 110,000 - 170,000; Full time

Job summary

Gigapower is seeking an Embedded AI Engineer in Dallas, TX to serve as the dedicated AI partner for the Finance organization. You will design and deploy AI-powered automations, RAG applications, agents, copilots, and internal productivity tools to enhance planning, forecasting, reporting, and decision-making.

You will work with Finance and Data Engineering teams to identify high-impact use cases, drive adoption, and measure business outcomes.

Qualifications

• Bachelor’s degree or equivalent experience.
• 1–3 years building software, analytics, automation, data or AI solutions.
• Hands-on with LLMs, prompt engineering, RAG, AI agents or automation workflows.
• Strong Python proficiency.
• Working SQL and structured data experience.

Responsibilities

• Collaborate with Finance to understand budgeting, forecasting, reporting and workflows.
• Identify AI use cases to improve financial analysis and decision making.
• Design and deploy AI-powered automations, agents, and productivity tools.
• Streamline reporting, forecasting and cost analysis through solutions.
• Partner with Data Engineering and AI teams on enterprise platforms.
• Build tools to increase visibility into spend, capital deployment, and performance.
• Coach stakeholders on Copilot, Claude, ChatGPT usage and adoption.
• Track adoption, quality, and business outcomes for continuous improvement.
• Reduce manual effort using workflow automation and intelligent reporting.
• Identify scalable AI opportunities across business functions.

Skills

Python

SQL

LLMs

RAG

AI agents

Automation

Education

Bachelor’s degree or equivalent experience

Tools

Azure

Snowflake

Microsoft Copilot

ChatGPT

Claude

Job description

Gigapower is seeking an Embedded AI Engineer in Dallas, TX to serve as the dedicated AI partner for the Finance organization. You will design and deploy AI-powered automations, RAG applications, agents, copilots, and internal productivity tools to enhance planning, forecasting, reporting, and decision-making.

You will work with Finance and Data Engineering teams to identify high-impact use cases, drive adoption, and measure business outcomes.