Description

Embedded AI Engineer - Supply Chain & Admin

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 Supply Chain & Administrative Services. This role is responsible for identifying, developing, and deploying AI-powered solutions that improve procurement, inventory management, materials planning, logistics, vendor coordination, and operational efficiency, while also supporting Legal and Human Resources functions through intelligent automation and workflow optimization. Working directly with business stakeholders, the Embedded AI Engineer will uncover high-value opportunities, build practical AI solutions, and drive AI adoption across critical support functions.

Key Responsibilities
• Partner with Supply Chain, Procurement, Logistics, Legal, and HR teams to understand workflows, challenges, and opportunities for AI-driven improvement.
• Identify and prioritize opportunities where AI can improve operational efficiency, decision-making, and service delivery.
• Build and deploy AI-powered automations, retrieval-augmented generation (RAG) applications, agents, copilots, and internal productivity tools.
• Develop solutions that improve procurement processes, inventory visibility, materials forecasting, logistics coordination, and vendor management.
• Create intelligent tools that streamline contract review, policy management, documentation, onboarding, and administrative workflows.
• Collaborate with Data Engineering and AI teams on enterprise-scale platforms and shared data initiatives.
• Coach stakeholders on effective use of Microsoft Copilot, Claude, ChatGPT, and other AI technologies.
• Measure solution adoption, quality, and business outcomes and continuously improve delivered capabilities.
• Reduce manual effort through workflow automation, reporting enhancements, and knowledge management solutions.
• Identify scalable AI use cases that can be leveraged across multiple corporate functions.

Qualifications
• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Supply Chain Management, Business, or a related discipline, or equivalent practical 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 working with structured datasets.
• Ability to take solutions from concept through deployment and user adoption.
• Strong communication skills and ability to build trusted relationships with non-technical stakeholders.
• Self-starter mindset with comfort operating in fast-paced and ambiguous environments.
• Strong analytical, problem-solving, and critical-thinking skills.
• Enthusiasm for learning complex business processes and applying technology to solve operational challenges.

Preferred Qualifications
• Experience in supply chain, procurement, inventory management, logistics, sourcing, or vendor management environments.
• Experience supporting legal operations, HR operations, employee services, or administrative functions is a plus.
• Familiarity with telecommunications, fiber broadband, construction, infrastructure, or field operations environments.
• Experience with Azure, Snowflake, cloud analytics platforms, or enterprise business systems.
• Experience with change management, training, enablement, or technology adoption initiatives.

Key Competencies:
• Supply Chain Optimization: Improves procurement, inventory, logistics, and operational performance through technology and automation.
• AI Solution Development: Designs and delivers practical AI-powered solutions that create measurable business value.
• Business Partnership: Builds trusted relationships across corporate functions and aligns solutions to business priorities.
• Process Automation: Identifies inefficiencies and develops scalable solutions that reduce manual work and improve productivity.
• Data-Driven Decision Making: Uses data, analytics, and AI to generate actionable insights and recommendations.
• Communication & Influence: Clearly explains technical concepts and drives adoption across diverse stakeholder groups.
• Learning Agility: Quickly develops expertise in new business domains, processes, and technologies.