Principal Engineer, AI Systems

OneStudyTeam

About The Position

At OneStudyTeam (a Reify Health company), we specialize in speeding up clinical trials and increasing the chance of new therapies being approved with the ultimate goal of improving patient outcomes. Our cloud-based platform, StudyTeam, brings research site workflows online and enables sites, sponsors, and other key stakeholders to work together more effectively. StudyTeam is trusted by the largest global biopharmaceutical companies, used in over 6,000 research sites, and is available in over 100 countries. Join us in our mission to advance clinical research and improve patient care. One mission. One team. That’s OneStudyTeam. As a Principal Engineer, AI Systems, you will serve as the organization's senior expert in the implementation, integration, and operational enablement of Artificial Intelligence systems. You will guide the deployment and support of OpenAI ChatGPT, Anthropic Claude, internally developed AI-enabled solutions, and other large language model (LLM) technologies across the enterprise. This role blends strategy and execution. You will work cross-functionally with engineering, operations, security, and business teams to identify AI-driven efficiency opportunities, implement solutions, and establish governance practices that ensure safe, compliant, and ethical use of AI. You will operate as a hybrid product manager, systems engineer, DevOps engineer, and enterprise AI advisor, shaping the organization's approach to intelligent automation and advanced tooling.

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, or related field (or equivalent practical experience)
Certifications in cloud platforms (AWS, Azure), AI/ML, or information security
10+ years of hands-on experience in software engineering, systems integration, or DevOps
3+ years of experience implementing and managing AI or automation tools in enterprise environments
Deep understanding of AI deployment frameworks
Experience integrating AI systems with enterprise applications, APIs, and data infrastructure
Strong Python and scripting skills for automation and AI orchestration
Proven ability to translate business problems into AI-enabled technical solutions
Familiarity with HIPAA, ISO 27001/27002, and secure software development practices
Working knowledge of NIST AI RMF 1.0 and EU AI Act risk categorization principles
Demonstrated ability to work cross-functionally and communicate technical solutions to non-technical audiences
Experience leading AI governance, security, or compliance initiatives in regulated industries

Nice To Haves

Experience with MLOps, data pipelines, or enterprise automation platforms such as Zapier and Make
Prior experience developing or managing chatbot workflows, prompt engineering, or AI knowledge bases
Familiarity with productivity-enhancing tools such as Microsoft Copilot, Slack AI, Salesforce AI, or similar enterprise AI integrations

Responsibilities

AI Enablement and Strategy: Lead organization-wide AI adoption and enablement initiatives. Identify opportunities to leverage AI tools to improve efficiency, accuracy, and productivity across business units.
Solution Design and Prototyping: Architect, configure, and prototype solutions using LLMs, APIs, and orchestration tools. Develop proof-of-concepts for department-specific AI use cases.
Systems Integration: Integrate AI capabilities into existing applications, workflows, and cloud environments (e.g., Azure, AWS). Manage connections between enterprise systems and AI platforms through APIs or automation layers.
AI Platform Management: Oversee configuration and operational support of platforms such as OpenAI, Anthropic, Zapier, and Make.
Security and Compliance Oversight: Ensure AI implementations adhere to internal policies and external standards, including HIPAA, ISO 27001/27002, and internal data governance frameworks.
Responsible AI and Risk Management: Implement and promote compliance with frameworks such as NIST AI RMF 1.0 and the EU AI Act. Conduct AI risk assessments and recommend mitigation controls.
Cross-Functional Collaboration: Partner with department heads and technical teams to evaluate requirements, recommend AI-enabled tools, and support implementation.
Education and Advocacy: Serve as a trusted AI advisor to business and technical leaders. Provide internal guidance, training, and documentation on AI tool usage, safety, and best practices.
Performance Monitoring: Establish metrics to evaluate AI-driven efficiency gains, user adoption, and business impact.
Vendor and Tool Evaluation: Continuously research, evaluate, and recommend new AI tools, frameworks, and integration strategies aligned with enterprise goals.