Engineer, Enterprise AI

Role Overview

• Design, build, and maintain enterprise AI solutions and services that enable the scalable adoption of generative AI, machine learning, and agentic AI capabilities across the organization.
• Implement enterprise AI architecture patterns and technical standards defined by the Enterprise AI Architect, translating reference architectures and design patterns into production-ready solutions.
• Develop and support AI integration patterns that connect AI capabilities with enterprise applications, APIs, data platforms, and cloud services.
• Build and maintain AI-enabled services and components, including model interfaces, orchestration services, agent frameworks, and reusable AI tooling for enterprise teams.
• Support the implementation of Agentic AI workflows, including orchestration, tool integration, context management, and human-in-the-loop capabilities.
• Implement and maintain AI operational capabilities (MLOps/LLMOps) including model deployment pipelines, monitoring, observability, lifecycle management, and operational controls.
• Ensure AI solutions align with enterprise AI governance, responsible AI standards, and regulatory requirements, including data privacy, auditability, and model transparency.
• Support AI platform development and enablement, working with Platform Engineering and Data Engineering teams to deploy, scale, and maintain enterprise AI infrastructure and tooling.
• Other duties as assigned.

Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems, or a related technical field, or equivalent work experience, required.
• Certification/Licenses: AWS Certified Solutions Architect – Associate, AWS Machine Learning – Specialty, or equivalent cloud-based AI/ML certification preferred.
• MLOps, AI platform engineering, or machine learning engineering certification preferred.
• Responsible AI, AI governance, or AI ethics training/certification preferred.
• 6-8 years of experience in software development, platform engineering, or machine learning engineering, including a minimum of 2-4 years of hands-on experience developing, integrating, or operationalizing Artificial Intelligence and Machine Learning solutions in production environments required.
• Experience building or supporting AI-enabled applications, data pipelines, model integrations, or AI platform components within cloud or distributed systems environments required.
• Experience implementing AI integration patterns that connect AI capabilities with enterprise applications, APIs, data platforms, and cloud services required.
• Experience developing or supporting generative AI and agentic AI workflows, including orchestration frameworks, tool integrations, context management, Model Context Protocol (MCP) servers or similar context services, and human-in-the-loop patterns to support governed AI decision-making required.
• Experience implementing or supporting AI operational practices (MLOps/LLMOps) including model deployment pipelines, monitoring, observability, lifecycle management, and operational controls required.
• Experience working within enterprise architecture standards and development frameworks, ensuring solutions aligned with architectural guardrails, security requirements, and platform standards required.
• Experience supporting AI governance and responsible AI practices, including data privacy, model transparency, auditability, and compliance with enterprise and regulatory standards required.
• Experience collaborating with architecture, engineering, data, and product teams to design and implement scalable AI-enabled solutions required.
• Experience developing and supporting cloud-based services, APIs, and distributed systems that enable scalable AI capabilities and enterprise platform integrations required.
• Strong development experience in modern programming languages, including Python, C#, or similar backend languages used for AI services and integrations required.
• Proven ability to interview end-users for insight on functionality, interface, problems, and/or usability issues required.
• Knowledge of PBM systems, claims adjudication processes, and data exchange patterns between payers, providers, and pharmacies preferred.
• Participate in, adhere to, and support compliance program objectives.
• The ability to consistently interact cooperatively and respectfully with other employees.

Tech Stack

• AWS
• Cloud
• Distributed Systems
• Python

Benefits

• Top of the industry benefits for Health, Dental, and Vision insurance
• 20 days paid time off
• 4 weeks paid parental leave
• 9 paid holidays
• 401K company match of up to 5%
• No vesting requirement
• Adoption Assistance Program
• Flexible Spending Account
• Educational Assistance Plan and Professional Membership assistance
• Referral Bonus Program – up to $750!