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.

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!

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI solutionsgenerative AImachine learningMLOpsAI integration patternsmodel deployment pipelinesorchestration frameworksdata pipelinescloud servicesPython

Soft Skills

collaborationcommunicationproblem-solvinguser insight gatheringrespectful interactionorganizational skillsadaptabilityteamworkleadershipcritical thinking

Certifications

AWS Certified Solutions Architect – AssociateAWS Machine Learning – SpecialtyMLOps certificationAI platform engineering certificationResponsible AI trainingAI governance certificationAI ethics certification