• Irving, TX
    3 days ago

    Job Description

    Why GM Financial Technology

    Innovation isn't just a talking point at GM Financial, it's how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We're committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.

    Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.

    What makes You an ideal candidate?

    • Expertise in software engineering that includes architecture, development, and testing experience.
    • Experience in a leadership capacity with direct mentorship or owning end to end solution delivery.
    • Proven experience delivering production Generative AI applications using agentic architectures, RAG, and orchestration frameworks.
    • Strong proficiency in Python and additional experience with C# or Java.
    • Familiarity with LangChain, LlamaIndex, or similar frameworks used for orchestration and agent-based systems.
    • Experience designing microservices, APIs, automated deployment pipelines, and scalable distributed systems.
    • Strong communication skills and the ability to explain and justify architectural decisions to technical and non-technical audiences.
    • Ability to craft clear deliverables such as presentations, using diagramming tools, reports and visual communication materials.

    Additional Knowledge and Skills

    • Working effectively within an AI enabled environment:
    • Ability to use AI tools (e.g., Microsoft Copilot) to support daily work
    • Skills in evaluating AI outputs for accuracy, compliance, and bias
    • Experience integrating AI into workflows to improve efficiency or insights
    • Familiarity with AI assisted research, summarization, and content generation
    • Understanding of responsible AI use, including ethics and data protection

    Experience & Education

    • Greater than 10 years in software engineering required, 2+ years in Gen AI and/or Agentic AI preferred

    • 3-5 years leading through mentorship in Gen AI and/or Agentic AI required

    • 3-5 years leading projects and initiatives through influence required

    • High School Diploma or equivalent required

    • Bachelors Degree preferred

    What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.

    Our Culture: Our team members define and shape our culture - an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work - we thrive.

    Compensation: Competitive pay and bonus eligibility.

    Work Life Balance: Flexible hybrid work environment, 2 days a week in the office.

    #GMFJobs #LI-Hybrid #LI-ST1

    About the role:

    Seeking a hands-on Principal Engineer to lead the strategy, design, and production deployment of agentic voice solutions using Genesys within a contact center environment. This role requires AWS expertise, Azure familiarity, telephony experience, and the ability to partner with vendors while building, scaling, and optimizing voice bot solutions for enterprise use. The Principal AI Engineer is also a hands‑on technical leader and thought partner who guides teams in designing, building, and delivering enterprise‑grade Generative AI solutions, including agentic systems, multi‑agent orchestration, and Retrieval‑Augmented Generation architectures. This role partners closely with product, enterprise architecture, security, and engineering leadership to ensure AI capabilities are scalable, reliable, compliant, and aligned with organizational standards. Success requires strong technical judgment, the ability to mentor and grow engineering talent, and a commitment to advancing responsible AI adoption across the enterprise.

    In this role, you will:

    • Guide and grow an AI engineering team by fostering technical excellence, accountability, continuous learning, and strong architectural decision‑making; support hiring, onboarding, and skills development.

    • Design, build, and deliver production‑ready Generative AI solutions, including agentic and multi‑agent systems, RAG pipelines, orchestration frameworks, APIs, microservices, automated pipelines, and testing, with hands‑on contribution in Python, C#, or Java as needed.

    • Define and standardize AI architecture, patterns, libraries, and development practices, selecting and applying Agentic Voicebots, Telephony, etc.

    • Ensure AI solutions are secure, compliant, and responsible by embedding privacy, data governance, auditability, PII protection, risk mitigation, and model evaluation in collaboration with security, legal, compliance, and data governance teams.

    • Partner with product, architecture, and engineering stakeholders to drive aligned solution direction, predictable delivery, and organization‑wide adoption of AI best practices.

    • Drive innovation and thought leadership through continuous exploration of emerging Generative AI technologies, experimentation, proof‑of‑concepts, and internal knowledge sharing.

    About the role:

    Seeking a hands-on Principal Engineer to lead the strategy, design, and production deployment of agentic voice solutions using Genesys within a contact center environment. This role requires AWS expertise, Azure familiarity, telephony experience, and the ability to partner with vendors while building, scaling, and optimizing voice bot solutions for enterprise use. The Principal AI Engineer is also a hands‑on technical leader and thought partner who guides teams in designing, building, and delivering enterprise‑grade Generative AI solutions, including agentic systems, multi‑agent orchestration, and Retrieval‑Augmented Generation architectures. This role partners closely with product, enterprise architecture, security, and engineering leadership to ensure AI capabilities are scalable, reliable, compliant, and aligned with organizational standards. Success requires strong technical judgment, the ability to mentor and grow engineering talent, and a commitment to advancing responsible AI adoption across the enterprise.

    In this role, you will:

    • Guide and grow an AI engineering team by fostering technical excellence, accountability, continuous learning, and strong architectural decision‑making; support hiring, onboarding, and skills development.

    • Design, build, and deliver production‑ready Generative AI solutions, including agentic and multi‑agent systems, RAG pipelines, orchestration frameworks, APIs, microservices, automated pipelines, and testing, with hands‑on contribution in Python, C#, or Java as needed.

    • Define and standardize AI architecture, patterns, libraries, and development practices, selecting and applying Agentic Voicebots, Telephony, etc.

    • Ensure AI solutions are secure, compliant, and responsible by embedding privacy, data governance, auditability, PII protection, risk mitigation, and model evaluation in collaboration with security, legal, compliance, and data governance teams.

    • Partner with product, architecture, and engineering stakeholders to drive aligned solution direction, predictable delivery, and organization‑wide adoption of AI best practices.

    • Drive innovation and thought leadership through continuous exploration of emerging Generative AI technologies, experimentation, proof‑of‑concepts, and internal knowledge sharing.

    Numbers & Facts

    LocationIrving, TX

    Skills

    • Adoptionunmatched
    • Amazon Web Services (AWS)unmatched
    • Application Programming Interface (API)unmatched
    • Architectural Servicesunmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Best Practicesunmatched
    • Call Centersunmatched
    • Cloud Computingunmatched
    • Communication Skillsunmatched
    • Customer Relationsunmatched
    • Distributed Computingunmatched
    • Emerging Technologyunmatched
    • Enterprise Architectureunmatched
    • Enterprise Protectionunmatched
    • Establish Prioritiesunmatched
    • Genesys Solutionsunmatched
    • Information/Data Security (InfoSec)unmatched
    • Javaunmatched
    • Leadershipunmatched
    • Legalunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Microservicesunmatched
    • Microsoft C# (C Sharp)unmatched
    • Microsoft Product Familyunmatched
    • Microsoft Windows Azureunmatched
    • Onboardingunmatched
    • Python Programming/Scripting Languageunmatched
    • Risk Managementunmatched
    • Risk Modelingunmatched
    • Security Architectureunmatched
    • Software Engineeringunmatched
    • Standards Developmentunmatched
    • Systems Scalabilityunmatched
    • Technical Leadershipunmatched
    • Telephonyunmatched
    • Test Automationunmatched
    • Test Plan/Scheduleunmatched
    • Testingunmatched
    • Thought Leadershipunmatched
    • Visual Communicationunmatched
    • Voice Productsunmatched

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