Lead, Software Development AI Practice

Navitus Health Solutions, LLC•,

1d•$132,830 - $166,037•Remote

About The Position

Navitus is adding a Lead, Software Development AI Practice to own the software development and delivery AI enablement practice. The role sets the practice’s direction and supports AI adoption across delivery and developer teams by establishing scalable enablement methods, reusable tools, standards, training, communities of practice, and coaching. The goal is to improve software quality and measurably increase the efficiency of delivering software solutions for the business. The Lead serves as a subject matter expert on AI platforms, generative AI, and agentic workflows and serves on the overall AI Governance Board. Through hands-on coaching, demonstrations, proof-of-concept initiatives, and scalable enablement, the role develops Navitus’s AI practice. AI practices must align with enterprise architecture principles, security requirements, current and future Data Engineering states, and regulatory standards while enabling innovation and business value. The position is remote, with work limited to residents of the states and Washington, DC listed in the posting. The stated schedule is 8 AM–5 PM CT. Minimal travel may be required for meetings, training, or other business needs.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related field, or equivalent work experience.
At least 8 years of experience in software development or architecture.
At least 3 years of experience focused on Artificial Intelligence and Machine Learning technologies.
Demonstrated experience defining software development AI frameworks and tools, including coaching, practice rollout, and demonstrations.
Demonstrated experience leading or scaling generative AI, machine learning, or agentic AI capabilities from proof of concept through broader adoption.
Demonstrated experience applying security, privacy, data governance, and risk requirements to technology solutions in a regulated or data-sensitive environment.
Demonstrated experience influencing technical and business stakeholders and driving adoption across teams without relying solely on direct reporting authority.

Nice To Haves

AWS Certified Solutions Architect Professional certification.
AWS Certified Machine Learning – Specialty certification.
Responsible AI or AI Governance certification.
Industry-recognized Certified AI Professional certification or equivalent AI/ML certification.

Responsibilities

Partner with Software Development and Delivery, Architecture, Security, Data Services, and business stakeholders to identify and prioritize high-value AI use cases that improve software quality, engineering productivity, operational efficiency, and business outcomes.
Establish reusable AI patterns, reference architectures, integration approaches, and development standards for generative AI, machine learning, and agentic AI capabilities.
Build and maintain AI-enabled services and components, including model interfaces, orchestration services, agent frameworks, prompt and tooling patterns, and reusable developer enablement assets.
Lead proof-of-concept and pilot initiatives, demonstrating practical AI value and turning successful experiments into repeatable capabilities for broader adoption.
Provide hands-on coaching, demonstrations, and day-to-day enablement to developers, delivery roles, and product teams on effective AI tools, tactics, and responsible usage.
Serve as the primary AI adoption point of contact for Software Development and Delivery, influencing teams through expertise, practical value, and partnership rather than direct reporting authority.
Ensure AI solutions comply with enterprise AI governance, responsible AI standards, security requirements, data privacy expectations, auditability needs, and model transparency principles.
Support agentic AI workflows, including orchestration, tool integration, context management, workflow design, and human-in-the-loop controls.
Own AI adoption measurement, including tools, metrics, reporting, training, and leadership updates that demonstrate usage, quality improvement, efficiency gains, and business impact.
Evaluate emerging AI platforms, tools, and capabilities for fit with enterprise architecture, security, scalability, interoperability, cost, and Software Development and Delivery needs, and recommend appropriate adoption approaches.
Participate in, adhere to, and support compliance program objectives.
Interact consistently and cooperatively and respectfully with other employees.
Perform other duties as assigned.