Paycom Online
Overview
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 degree in Computer Science, Machine Learning, Artificial Intelligence, or related field. Experience: Familiarity with data engineering and data governance principles. Experience defining and implementing enterprise AI strategy in complex organizations. Track record of mentoring engineering and data science teams on AI best practices. Strong communication skills to present complex AI concepts to executive stakeholders. PHYSICAL DEMANDS
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to stand; walk; sit; use hands and fingers to handle, type, or feel; reach with hands and arms; and talk or hear. The employee may occasionally lift and/or move up to 25 pounds. Specific vision abilities required by this job include close vision and ability to adjust focus. WORK ENVIRONMENT AND ENVIRONMENTAL CONDITIONS
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. No hazardous or significantly unpleasant conditions. The noise level in the work environment is usually moderate.
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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 degree in Computer Science, Machine Learning, Artificial Intelligence, or related field. Experience: Familiarity with data engineering and data governance principles. Experience defining and implementing enterprise AI strategy in complex organizations. Track record of mentoring engineering and data science teams on AI best practices. Strong communication skills to present complex AI concepts to executive stakeholders. PHYSICAL DEMANDS
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to stand; walk; sit; use hands and fingers to handle, type, or feel; reach with hands and arms; and talk or hear. The employee may occasionally lift and/or move up to 25 pounds. Specific vision abilities required by this job include close vision and ability to adjust focus. WORK ENVIRONMENT AND ENVIRONMENTAL CONDITIONS
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. No hazardous or significantly unpleasant conditions. The noise level in the work environment is usually moderate.
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