Embedded AI Engineer - Finance

Gigapower•Dallas, TX

18h•Remote

About The Position

The Embedded AI Engineer serves as the dedicated AI partner for Gigapower's Finance organization. This role is responsible for identifying, developing, and deploying AI-powered solutions that improve financial planning, forecasting, capital strategy, funding analysis, build-cost approvals, reporting, and decision-making across the business. Working directly with Finance, FP&A, and business leaders, the Embedded AI Engineer will uncover high-value opportunities for automation, insight generation, and workflow optimization while driving adoption of AI throughout the finance function.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Finance, or a related discipline, or equivalent experience.
1 to 3 years of experience developing software, analytics, automation, data, or AI-based solutions.
Hands-on experience with LLMs, prompt engineering, RAG, AI agents, or automation workflows.
Strong proficiency in Python.
Working knowledge of SQL and experience with structured datasets.
Ability to take solutions from concept through deployment and user adoption.
Strong communication and stakeholder management skills.
Self-starter mindset with comfort operating in fast-paced and ambiguous environments.
Strong analytical, problem-solving, and critical-thinking skills.
Enthusiasm for learning complex financial and business processes.

Nice To Haves

Experience in corporate finance, FP&A, capital planning, financial analytics, or infrastructure cost estimation.
Experience supporting telecommunications, construction, utilities, infrastructure, or capital-intensive industries.
Experience with Azure, Snowflake, cloud analytics platforms, or modern data environments.
Experience with change management, user enablement, training, or technology adoption initiatives.

Responsibilities

Partner with Finance teams to understand budgeting, forecasting, capital planning, reporting, and approval workflows.
Identify and prioritize opportunities where AI can improve financial analysis, operational efficiency, and decision-making.
Build and deploy AI-powered automations, RAG applications, agents, copilots, and internal productivity tools.
Develop solutions that streamline financial reporting, forecasting, cost analysis, and capital approval processes.
Collaborate with Data Engineering and AI teams on enterprise-scale platforms and shared data initiatives.
Create tools that improve visibility into spend, capital deployment, project economics, and business performance.
Coach stakeholders on effective use of Microsoft Copilot, Claude, ChatGPT, and other AI technologies.
Measure adoption, quality, and business outcomes to continuously improve delivered solutions.
Reduce manual effort through workflow automation and intelligent reporting capabilities.
Identify scalable AI use cases that can be deployed across multiple business functions.