Paycom is seeking an AI Architect to build innovative AI solutions and shape a product from the ground up, serving as a trusted advisor on AI strategy and implementation.
Requirements
- 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.
- Experience in deploying and scaling containerized, distributed software and AI systems using tools such as Kubernetes.
- Depth in using LLMs, including training, fine-tuning, and evaluation. Historical background in “traditional” NLP tools
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.
Other
- Self-motivated
- Passion for building innovative products and driving beyond expectations
- Demonstrated ability to influence and align cross-functional teams in technical and business domains.
- Ability to tactfully and effectively give and receive concrete feedback.
- Strong communication skills to present complex AI concepts to executive stakeholders.
