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Principal AI Architect
Job in
Oklahoma City, Oklahoma County, Oklahoma, 73116, USA
Listed on 2026-01-06
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)
- Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or related field
- 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
- Masters…
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