Engineer, Enterprise AI

Navitus; Tallahassee (FL); Remote; USD 120,000 - 170,000; Full time

Benefits offered by this job

Health, Dental, and Vision insurance

20 days paid time off

4 weeks paid parental leave

9 paid holidays

401K company match up to 5%

Adoption Assistance Program

Flexible Spending Account

Educational Assistance and Memberships

Referral Bonus Program – up to $750

Job summary

Navitus is seeking an Engineer, Enterprise AI to design, build, and operate enterprise AI capabilities that enable scalable adoption of generative AI, ML, and agentic AI across the organization.

You will translate enterprise AI architectures into production-ready solutions, partnering with Enterprise Architecture, Platform, Data, and Product teams to deliver AI services and governance frameworks that support AI-enabled workflows and secure, compliant deployments.

Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems, or related 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 2-4 years hands-on experience deploying AI/ML solutions in production, 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 connecting AI to enterprise apps, APIs, data platforms, and cloud services required.
• Experience developing or supporting generative AI and agentic AI workflows, including orchestration frameworks, context management, MCP servers, and human-in-the-loop patterns to support governance, required.
• Experience implementing or supporting AI operational practices (MLOps/LLMOps) including model deployment pipelines, monitoring, observability, lifecycle management, and controls, required.
• Experience working within enterprise architecture standards and development frameworks, ensuring solutions align with guardrails, security, and platform standards required.
• Experience supporting AI governance and responsible AI practices, including data privacy, model transparency, auditability, and compliance with enterprise/regulatory standards required.
• Experience collaborating with architecture, engineering, data, and product teams to design scalable AI-enabled solutions required.
• Experience developing and supporting cloud-based services, APIs, and distributed systems enabling scalable AI capabilities and enterprise integrations required.
• Strong development experience in 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 usability required.
• Knowledge of PBM systems, claims adjudication processes, and data exchange patterns between payers, providers, and pharmacies preferred.
• Participate in and support compliance program objectives.
• The ability to consistently interact cooperatively and respectfully with other employees.

Responsibilities

• Design, build, and maintain enterprise AI solutions and services enabling scalable adoption of generative AI, machine learning, and agentic AI across the organization.
• Implement enterprise AI architecture patterns and technical standards defined by the Enterprise AI Architect, translating reference architectures into production-ready solutions.
• Develop and support AI integration patterns connecting 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 governance, responsible AI standards, and regulatory requirements, including data privacy, auditability, and model transparency.
• Support AI platform development and enablement, working with Platform/Data Engineering teams to deploy, scale, and maintain enterprise AI infrastructure.
• Other duties as assigned.

Skills

Python

C#

Software development

MLOps

Education

Bachelor's degree in Computer Science or related field

Tools

AWS Certified Solutions Architect – Associate

AWS Machine Learning – Specialty

MLOps certification

Job description

Overview

Due to growth, we are adding a Engineer, Enterprise AIto our team!

The Engineer, Enterprise AI is responsible for designing, building, and operationalizing enterprise AI capabilities that enable the scalable adoption of Artificial Intelligence and Agentic AI across the organization. Working closely with the Enterprise AI Architect, this role translates enterprise AI architecture, patterns, and governance standards into implementable solutions and reusable technical components while partnering with Enterprise Architecture, Platform Engineering, Data Engineering, and Product teams to develop AI services, integrations, and operational frameworks that support generative AI, machine learning, and agentic workflows. The Engineer ensure AI solutions are implemented in alignment with enterprise architecture standards, security requirements, and regulatory compliance while enabling teams across the organization to safely and effectively leverage AI technologies to deliver business value.

Is this you? Find out more below!

Responsibilities

How do I make an impact on my team?

• 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.

Qualifications

What our team expects from you?

• 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.

What can you expect from Navitus?

• 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!

#LI-Remote

Navitus Health Solutions is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, creed, sex, pregnancy, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by law.

Equal employment opportunity, including veterans and individuals with disabilities.

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