Lead Technical Architect (AI)

TL;DR

Lead Technical Architect (AI/Python): Designing and guiding the system architecture for enterprise AI platforms and services with an accent on scalability, security, and enterprise integration. Focus on translating business needs into technical solutions, leading proof-of-concept (POC) efforts, and ensuring compliance with healthcare regulatory standards.

Location: Remote (Must be based in Pennsylvania, USA)

Company

hirify.global is a leading healthcare organization leveraging AI-driven innovation to deliver cutting-edge infrastructure and services.

What you will do

• Lead the end-to-end technical vision, system design, and solution architecture for enterprise-grade AI platforms.
• Translate business requirements into robust, scalable, and maintainable technical solutions.
• Implement enterprise integrations using APIs, messaging systems, and data pipelines in heterogeneous environments.
• Lead proof-of-concept (POC) efforts to validate the feasibility and business value of new technologies.
• Provide technical leadership and mentorship to engineering and project teams.
• Present architectural designs and strategic directions to the Architecture Review Board.

Requirements

• 8+ years of experience in software development, solution architecture, or enterprise systems design.
• Strong programming skills in Python for building production-grade systems.
• 2+ years of hands-on experience with cloud platforms, with a preference for Google Cloud Platform (GCP).
• Proven expertise in designing secure enterprise integrations and data pipelines.
• Must be based in Pennsylvania, USA.
• Familiarity with HIPAA and other healthcare IT regulatory standards.

Nice to have

• Experience with DevOps, MLOps, Containerization, and Infrastructure as Code (IaC).
• Master's Degree in Information Technology or a closely related field.
• Industry certifications such as Enterprise Architect (SCEA) or Project Management.

Culture & Benefits

• Highly collaborative, innovative, and results-oriented team environment.
• Strong emphasis on continuous learning and open communication.
• Commitment to excellence in building the future of AI in healthcare.
• Flexible remote work arrangement (Working at Home).