Description

Embedded AI Engineer - Engineering

Company: Gigapower LLC
Dept./Org.: Trans./Strategy
Location: Virtual (Remote)
Position Type: PW

Position Summary

The Embedded AI Engineer serves as the dedicated AI partner for Gigapower's Engineering teams. This role is responsible for identifying, developing, and deploying AI-powered solutions that improve engineering workflows across permit design, high-level design (HLD), low-level design (LLD), network planning, and engineering operations.

Working directly with fiber network engineers, designers, and permitting teams, the Embedded AI Engineer will uncover high-value opportunities to automate manual processes, improve design quality, accelerate project delivery, and enhance decision-making through AI-powered solutions. The ideal candidate combines strong technical expertise with the ability to build trusted relationships across engineering teams and translate complex operational challenges into practical AI capabilities.

This position offers a unique opportunity to own AI strategy and execution for a critical technical function while helping shape the future of broadband network design and engineering at Gigapower.

Key Responsibilities
• Partner with Engineering, Design, and Permitting teams to understand workflows, challenges, and opportunities for AI-driven improvement.
• Identify, prioritize, and deliver AI solutions that improve engineering productivity, design quality, permitting efficiency, and project execution.
• Build and deploy AI-powered automations, retrieval-augmented generation (RAG) applications, intelligent agents, copilots, and internal engineering tools.
• Develop solutions that streamline permit package creation, engineering documentation, design reviews, and standards compliance.
• Create AI-enabled capabilities that assist with HLD and LLD development, engineering analysis, and network planning activities.
• Collaborate with Data Engineering and AI teams on enterprise-scale solutions involving shared platforms, analytics, and operational data.
• Coach engineering stakeholders on effective use of AI tools including Microsoft Copilot, Claude, and ChatGPT.
• Measure solution adoption, quality, and business impact, continuously improving capabilities based on stakeholder feedback.
• Partner with engineering leadership to identify scalable AI opportunities across network design and deployment activities.
• Utilize AI-powered tools to improve personal productivity and accelerate solution development.

Qualifications
• Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience.
• 1 to 3 years of experience developing software, analytics, automation, or AI-based solutions.
• Hands-on experience building applications utilizing Large Language Models (LLMs), including prompting, retrieval-augmented generation (RAG), AI agents, automation workflows, or tool integrations.
• Strong proficiency in Python.
• Experience developing solutions from concept through deployment and user adoption.
• Working knowledge of SQL and experience working with structured datasets.
• Strong communication skills with the ability to explain technical concepts to non-technical audiences.
• Demonstrated ability to operate independently and manage competing priorities in a fast-paced environment.
• Strong problem-solving, analytical, and critical-thinking skills.
• Enthusiasm for learning new technologies and understanding complex business operations.

Preferred Qualifications
• Experience in fiber engineering, telecommunications engineering, network design, permitting, outside plant (OSP), or broadband infrastructure.
• Familiarity with high-level design (HLD), low-level design (LLD), fiber routing, network planning, or engineering documentation processes.
• Working knowledge of SQL and experience with structured, geospatial, or GIS-based datasets.
• Experience with Azure, Snowflake, cloud-based analytics platforms, or engineering systems.
• Experience supporting change management, technology adoption, enablement, or training initiatives.

Key Competencies
• Engineering Process Optimization: Identifies opportunities to improve engineering efficiency, quality, and consistency through technology.
• AI Solution Development: Designs and delivers practical AI-powered solutions that create measurable business value.
• Technical Partnership: Builds trusted relationships with engineers, designers, and technical stakeholders to solve complex operational challenges.
• Problem Solving & Analysis: Applies data-driven thinking and technical expertise to address engineering and network design challenges.
• Innovation & Automation: Continuously seeks opportunities to eliminate manual work and improve productivity through automation.
• Communication & Influence: Clearly explains technical concepts, gains stakeholder buy-in, and drives adoption of new capabilities.
• Learning Agility: Quickly learns new technologies, engineering processes, and business domains to maximize impact.