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Principal AI Architect

Job in Oklahoma City, Oklahoma County, Oklahoma, 73116, USA
Listing for: Paycom Online
Full Time position
Listed on 2026-01-06
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below

Paycom is seeking a self-motivated AI Architect with a passion for building innovative products and driving beyond expectations. In this role, you will collaborate closely with software engineers to deliver world-class AI solutions to our clients. This is a unique opportunity to shape a product from the ground up, work alongside a team of talented technologists, and serve as a trusted advisor on AI strategy and implementation.

RESPONSIBILITIES
  • Define architectural changes that can be implemented incrementally, while minimizing risk.
  • Collaborate with a variety of stakeholders to determine architectural priorities, especially in AI model deployment and MLOps workflows.
  • Design and implement autonomous or semi-autonomous AI agents capable of multi-step reasoning, decision-making, and tool orchestration.
  • Create innovative applications leveraging generative AI for text, data extraction, summarization, and reasoning tasks.
  • Define and evolve model governance, monitoring, drift detection and re-training workflows.
  • Advocate for security and ethical AI practices in compliance with OWASP ML Top 10 and relevant standards.
  • Design and evolve AI/ML pipelines and software architecture to support continuous delivery and model lifecycle management.
  • Automate batch inference workflows and integrate AI features into both internal tools and customer-facing products.
  • Partner with cross-functional teams to ensure AI solutions are reliable, scalable, and business-impactful.
  • Build, fix, and improve code, especially high-value AI/ML services and APIs
  • Architect, design, and implement scalable AI/ML systems across cloud and on premise environments.
  • Design advancements in architecture that move software and AI/ML pipelines forward.
  • Train team members on AI/ML practices, new techniques, and past mistakes.
  • Lead the design, development, and deployment of GenAI models and intelligent agents.
  • Architect and implement scalable AI/ML systems across cloud and on-premise environments.
  • Translate complex technical concepts into clear insights for non-technical stakeholders.
  • Mentor team members on AI/ML techniques, tooling and best practices.
  • Perform regular and thorough market research, both with our existing vendors, and prospective vendors to stay one step ahead of the latest trends in the AI space.
  • Define the test plan to collect data on accuracy, reliability, performance, power, and robustness of the design.
  • Contribute to technical conversations and documentation (e.g., white papers, schematics, FDD, HLDR)
Qualifications Education/Certification
  • Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or related field
Experience
  • Software engineer experienced building and architecting analytical software systems using AI and ML.
  • Experience developing software utilizing various languages, including Python, SQL and/or the ability to pick up new languages quickly.
  • Strong knowledge and experience using data platforms, machine learning frameworks and generative AI tooling.
  • Experience designing and deploying ML models to production and optimizing MLOps practices.
  • Experience with the full lifecycle of software and AI/ML development, including version control, build management, unit testing, CI/CD, API paradigms and model versioning.
  • Demonstrated ability to influence and align cross-functional teams in technical and business domains.
  • Ability to tactfully and effectively give and receive concrete feedback.
  • Experience in deploying and scaling containerized, distributed software and AI systems using tools such as Kubernetes.
  • Manages resource usage (GPU/CPU), scaling and access controls.
  • Depth in using LLMs, including training, fine-tuning, and evaluation. Historical background in “traditional” NLP tools
  • Experience in SOA, Modular Monolith Architecture, and distributed systems for AI training and inference
  • Familiarity with static analysis, code scanning, and ML-specific monitoring tools
  • Experience with prompt engineering, RAG, or agentic AI architecture
  • Experience with agentic frameworks in practice
  • Knowledgeable in responsible AI and security best practices, including OWASP Top 10 and OWASP ML Top 10
PREFERRED QUALIFICATIONS Education/Certification
  • Masters…
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