AI Software Engineer

Job Description

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.

• 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.