Applied AI Engineer

Gigapower

  • Dallas, TX
  • 2 days ago

    Highlights

    This role focuses on the application layer of AI, including retrieval-augmented generation (RAG), agents, orchestration frameworks, retrieval infrastructure, and internal tooling that enables scalable, secure, and cost-effective adoption of AI solutions across the enterprise. 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.

    Numbers & Facts

    LocationDallas, TX

    Description

    Applied AI Engineer

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

     

    Who We Are

    Gigapower 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 Applied AI Engineer serves as a senior individual contributor within Gigapower's AI organization, responsible for building and operating the shared AI platform, reusable AI services, and cross-functional AI capabilities that power innovation across the business. This role focuses on the application layer of AI, including retrieval-augmented generation (RAG), agents, orchestration frameworks, retrieval infrastructure, and internal tooling that enables scalable, secure, and cost-effective adoption of AI solutions across the enterprise. Working closely with Data Engineering and Embedded AI Engineers, the Applied AI Engineer transforms operational data, documents, and business knowledge into robust AI capabilities that can be leveraged across multiple business functions. 

    Key Responsibilities

    ·        Build and operate Gigapower’s shared AI platform, including internal AI gateways, retrieval infrastructure, and reusable AI services. 

    ·        Design, develop, deploy, and support end-to-end LLM applications utilizing orchestration frameworks, agents, prompt engineering, retrieval systems, and evaluation methodologies. 

    ·        Build and maintain scalable RAG solutions leveraging structured, unstructured, and geospatial data sources. 

    ·        Develop reusable components, APIs, frameworks, and tooling that accelerate AI adoption across multiple teams and business functions. 

    ·        Deploy and operate AI workloads within Azure cloud environments utilizing containerized architectures and modern deployment practices. 

    ·        Partner with Embedded AI Engineers on complex, cross-functional initiatives that span multiple business domains. 

    ·        Monitor solution quality, adoption, cost efficiency, reliability, and business impact, continuously refining capabilities as needed. 

    ·        Implement best practices for AI governance, observability, evaluation, and operational excellence. 

    ·        Optimize AI systems for cost, performance, scalability, and maintainability. 

    ·        Utilize AI-powered tools to improve personal productivity and accelerate software development and innovation. 

    Qualifications

    ·        Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related discipline, or equivalent practical experience. 

    ·        3 to 5 years of software engineering experience, including recent hands-on experience building LLM-based applications. 

    ·        Strong proficiency in Python. 

    ·        Demonstrated experience building and maintaining RAG systems, including embeddings, vector databases, retrieval architectures, and evaluation frameworks. 

    ·        Experience designing and deploying AI agents, orchestration frameworks, and production-grade AI applications. 

    ·        Experience deploying and operating services in cloud environments, preferably Microsoft Azure. 

    ·        Experience working with containerized platforms and modern application deployment approaches. 

    ·        Strong understanding of performance, scalability, reliability, and cost considerations associated with token-based AI systems. 

    ·        Working knowledge of SQL and experience utilizing structured and geospatial datasets. 

    ·        Strong analytical, problem-solving, and communication skills. 

    Preferred Qualifications

    ·        Experience with AI gateways, chat interfaces, and reusable AI platform architectures. 

    ·        Experience implementing evaluation frameworks, guardrails, governance controls, and AI safety capabilities. 

    ·        Experience working with geospatial data and location-based analytics. 

    ·        Experience with MLOps practices including deployment automation, monitoring, CI/CD, and operational support for AI systems. 

    ·        Experience supporting enterprise AI initiatives in data-intensive environments. 

    Key Competencies

    ·        AI Platform Engineering: Designs and maintains scalable, reusable AI capabilities that support enterprise-wide adoption. 

    ·        LLM Application Development: Builds robust production-grade solutions leveraging modern AI architectures and frameworks. 

    ·        Technical Leadership: Influences architecture, standards, and engineering best practices across teams. 

    ·        Cross-Functional Collaboration: Partners effectively with engineering, data, and business teams to deliver impactful solutions. 

    ·        Operational Excellence: Prioritizes reliability, observability, security, performance, and maintainability. 

    ·        Innovation & Automation: Continuously identifies opportunities to improve business outcomes through AI-enabled capabilities. 

    ·        Data-Driven Decision Making: Uses metrics, evaluation, and adoption data to guide continuous improvement. 

    About Us

    Gigapower is building the next generation of broadband infrastructure. Through innovative fiber network deployment and strategic partnerships, we are helping expand high-speed connectivity to communities and businesses across the United States. Our mission is to deliver reliable, scalable, and future-ready broadband solutions that empower economic growth, education, healthcare, and digital innovation.

    At Gigapower, we value collaboration, accountability, integrity, and continuous improvement. We are committed to creating an environment where employees can contribute meaningful work, develop professionally, and make a lasting impact on the communities we serve. As we continue to grow, we seek talented individuals who are passionate about excellence and eager to help shape the future of connectivity.

    EEO

    Gigapower is an Equal Opportunity Employer and is committed to creating a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, national origin, ancestry, citizenship status, age, disability, medical condition, genetic information, sex, pregnancy, sexual orientation, gender identity or expression, marital status, veteran status, military status, or any other characteristic protected by applicable federal, state, or local law.

    Gigapower is committed to providing reasonable accommodation to qualified individuals with disabilities and to applicants throughout the recruitment process. If you require assistance or accommodation, please notify a member of our Talent Acquisition team.

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