Embedded Ai Engineer Jobs (NOW HIRING)

Embedded AI Engineer – Construction (Project Management)

Location: Fully Remote

Compensation: $100k-$105k w/9% bonus

Job Description:

Client Is:

• Client is building next-generation fiber broadband infrastructure that expands high-speed connectivity to communities across the United States.
• We are committed to innovation, operational excellence, and leveraging technology to deliver smarter, faster, and more scalable solutions.
• As an AI-forward organization, we encourage employees at every level to embrace emerging technologies, continuously expand their AI capabilities, and actively incorporate AI tools into their daily work to improve productivity, decision-making, collaboration, and business outcomes.

Position Summary:

• The Embedded AI Engineer serves as the dedicated AI partner for Client's Construction Project Management organization.
• This role is responsible for identifying, developing, and deploying AI-powered solutions that improve project planning, scheduling, forecasting, coordination, reporting, and execution across Client's fiber deployment programs.
• Working directly with project managers and construction leaders, the Embedded AI Engineer will uncover high-value opportunities, build practical AI solutions, and drive AI adoption throughout the organization.

Key Responsibilities:

• Partner with Construction Project Management teams to understand planning, scheduling, forecasting, coordination, and execution workflows.
• Identify and prioritize opportunities where AI can improve project delivery, visibility, efficiency, and decision-making.
• Build and deploy AI-powered automations, RAG applications, agents, copilots, and internal tools.
• Develop solutions that enhance project scheduling, milestone tracking, risk identification, resource planning, and reporting.
• Collaborate with Data Engineering and AI teams on enterprise-scale solutions and platform initiatives.
• Coach stakeholders on effective use of AI tools including Microsoft Copilot, Claude, and ChatGPT.
• Measure solution adoption, quality, and business outcomes and continuously improve capabilities.
• Reduce administrative burden through workflow automation and intelligent reporting solutions.
• Identify repeatable solutions that can be scaled across additional Client business functions.
• 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 with Azure, Snowflake, GIS data, change management, enablement, or user training.

Key Competencies:

• Project Planning & Execution: Understands project delivery processes and develops solutions that improve planning, forecasting, and execution.
• AI Solution Development: Designs and delivers practical AI-powered capabilities that create measurable business value.
• Business Partnership: Builds trusted relationships with operational stakeholders and aligns solutions to business priorities.
• Process Optimization: Identifies inefficiencies and develops scalable approaches to improve operational performance.
• Data-Driven Decision Making: Uses data, analytics, and AI to generate actionable insights and recommendations.
• Communication & Influence: Explains technical concepts clearly and drives adoption across diverse stakeholder groups.
• Learning Agility: Quickly develops expertise in new technologies, processes, and business domains.