Engineer, Enterprise AI

atNavitus Health SolutionsRemote

Alaska Hawaii Maine New Hampshire New Mexico

Full-time Artificial IntelligenceMid-levelSenior$105.3k – $150k/year

Posted Aug 6

This is a fully remote position, open to applicants in Alaska, +12 more states.

📋 Description

• Design, develop, and maintain enterprise-level AI solutions and services for generative AI, machine learning, and agentic AI implementation.

• Apply enterprise AI architecture patterns and technical standards to produce production-ready solutions.

• Create and support AI integrations with enterprise applications, APIs, data platforms, and cloud services.

• Construct and sustain model interfaces, orchestration services, agent frameworks, and reusable AI tools.

• Facilitate Agentic AI workflows, encompassing orchestration, tool integration, context management, and human-in-the-loop functionalities.

• Establish and uphold MLOps/LLMOps capabilities, including deployment pipelines, monitoring, observability, lifecycle management, and operational oversight.

• Ensure compliance with AI governance, responsible AI standards, data privacy, auditability, model transparency, and regulatory obligations.

• Assist in AI platform development and enablement alongside Platform Engineering and Data Engineering teams.

• Carry out additional responsibilities as assigned.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems, or a related technical discipline, or equivalent practical experience, is required.

• A minimum of 6–8 years of experience in software development, platform engineering, or machine learning engineering is required.

• At least 2–4 years of hands-on experience in developing, integrating, or operationalizing AI/ML solutions within production settings is required.

• Proven experience in constructing AI-enabled applications, data pipelines, model integrations, or AI platform components in cloud or distributed systems environments.

• Demonstrated experience in implementing AI integration patterns with enterprise applications, APIs, data platforms, and cloud services.

• Experience in developing or supporting generative AI and agentic AI workflows, orchestration frameworks, tool integrations, context management, MCP servers or similar context services, and human-in-the-loop models.

• Familiarity with implementing or supporting MLOps/LLMOps practices, including deployment pipelines, monitoring, observability, lifecycle management, and operational controls.

• Background in working within enterprise architecture standards and development frameworks.

• Experience in supporting AI governance and responsible AI practices, including data privacy, model transparency, auditability, and regulatory adherence.

• Collaboration experience with architecture, engineering, data, and product teams.

• Proven experience in developing and supporting cloud-based services, APIs, and distributed systems.

• Strong programming skills in Python, C#, or similar backend languages.

• Capability to interview end-users regarding functionality, interfaces, issues, and usability concerns.

• Ability to engage in and support compliance program objectives.

• Capacity to interact cooperatively and respectfully with colleagues.

• AWS Certified Solutions Architect – Associate, AWS Machine Learning – Specialty, or an equivalent cloud-based AI/ML certification is preferred.

• Certification in MLOps, AI platform engineering, or machine learning engineering is preferred.

• Training or certification in Responsible AI, AI governance, or AI ethics is preferred.

• Knowledge of PBM systems, claims adjudication processes, and payer/provider/pharmacy data exchange patterns is preferred.

• Remote work is not available to residents of Alaska, Hawaii, Maine, Mississippi, New Hampshire, New Mexico, North Dakota, Rhode Island, South Carolina, South Dakota, West Virginia, and Wyoming.