Senior AI Engineer
Location: Tallahassee, FL (Hybrid)
The Senior AI Engineer is responsible for designing, developing, and deploying enterprise-grade Generative AI and automation solutions that transform internal operations, systems, and workflows. This role focuses on hands-on engineering and implementation, delivering secure, scalable, and compliant AI capabilities within NOVA's Azure Government (GCC High) environment, working across NOVA's hybrid AI/automation stack which includes Azure OpenAI Service, the N8N workflow automation platform, the OpenClaw personal AI assistant platform, Microsoft 365 GCC High, and the broader Microsoft Azure Government ecosystem.
Working within the IT organization, this individual will partner with IT leadership and architecture stakeholders to implement AI solutions aligned with enterprise standards and federal compliance requirements, while directly developing high-impact applications and automation capabilities. The Senior AI Engineer will also lead Agile / Scrum development practices for the AI and automation program, driving iterative delivery of value to the business.
Essential Functions Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The essential job functions for this position include:
Enterprise AI Architecture & Strategy
Contribute to the design and implementation of AI and automation solutions across NOVA's hybrid stack, including Azure OpenAI Service, N8N (workflow automation), OpenClaw (personal AI assistants), Microsoft 365 GCC High, and Azure Government, aligning with defined enterprise architecture and standards.
Contribute to and maintain a multi-year AI and automation roadmap aligned with enterprise IT strategy and federal compliance requirements.
Support implementation of AI governance, security, and usage policies in alignment with the NOVA AI Tool Program (Tier 0–Tier 3 model), CMMC 2.0, NIST SP 800-171, and DoD data protection requirements.
Ensure AI implementation meets enterprise identity, access management, and data security controls (e.g., Entra ID, RBAC, Conditional Access, managed identities).
Provide technical input into evaluation and selection of AI tools, models, and platforms appropriate for GCC High and Azure Government environments.
Hands-On AI Engineering & Solution Delivery
Design, build, and deploy Generative AI applications, copilots, agents, and automation workflows leveraging Azure OpenAI Service, N8N, OpenClaw, Microsoft Graph API, Power Platform, and Copilot Studio.
Develop and implement retrieval-augmented generation (RAG) solutions using enterprise data sources such as SharePoint Online (GCC High), Teams, document libraries, and internal knowledge repositories.
Build secure APIs, services, webhooks, and integrations connecting AI solutions to enterprise platforms and line-of-business systems.
Prototype and rapidly deploy high-value use cases that automate internal processes and improve productivity across business units.
Optimize AI systems for performance, cost, scalability, and secure operation within government cloud constraints, including managed identity authentication, private networking, and data residency requirements.
Develop reusable AI and automation components, services, integration patterns, and workflow templates to support scalable solution delivery.
Troubleshoot, debug, and continuously improve AI and automation systems in production environments, maintaining appropriate logging, monitoring, and alerting.
Enterprise Automation & Ecosystem Integration
Identify and implement automation solutions in collaboration with business stakeholders and IT leadership, prioritizing high-value, repeatable, cross-functional automations.
Integrate AI capabilities into enterprise tools to enhance collaboration, knowledge management, and operational efficiency.
Leverage Microsoft Graph, N8N connectors, OpenClaw skills, and other enterprise data connectors to integrate AI capabilities with line-of-business systems including ServiceNow, Salesforce, and similar enterprise SaaS platforms.
Partner with stakeholders across business units to redesign and modernize workflows using AI-enabled capabilities.
AI Governance, Security & Compliance
Implement responsible AI practices within an Azure Government / GCC High-compliant environment, including data protection, access controls, and usage policies.
Apply established guardrails and security controls to mitigate risks such as data leakage, prompt injection, model misuse, and insecure outputs.
Ensure developed solutions align with federal cybersecurity, privacy, and compliance standards, and with the NOVA AI Tool Program tiering model.
Support implementation of monitoring, logging, and auditing using Microsoft security and compliance tools (Purview, Defender, Sentinel) and platform-native logging (Azure Monitor, Log Analytics, SIEM).
Collaborate with cybersecurity teams to ensure AI and automation systems align with the organization's path toward CMMC 2.0 certification and enterprise security posture.
Technical Leadership & Agile Delivery
Serve as the enterprise subject matter expert for AI and automation engineering within NOVA's Azure Government / GCC High environment.
Lead Agile / Scrum development practices for the AI and automation program, including sprint planning, daily stand-ups, backlog grooming, sprint reviews, and retrospectives, ensuring iterative delivery of value to the business.
Maintain and prioritize the AI/automation product backlog in partnership with IT leadership and business stakeholders, translating business needs into well-defined user stories, acceptance criteria, and technical tasks.
Establish and enforce engineering practices including version control, code review, CI/CD, infrastructure-as-code, and documentation standards across the AI/automation portfolio.
Collaborate with IT leadership and architecture teams to align AI and automation solutions with enterprise strategy.
Lead internal adoption of AI capabilities, including training, enablement, and change management in partnership with business units.
Mentor IT staff and cross-functional teams on AI technologies, automation platforms, and modern engineering practices.
Communicate technical solutions and capabilities effectively to executive, technical, and non-technical stakeholders.
Other duties as required.
Competencies
Required skills and abilities to effectively perform this position include, but are not limited to:
Skilled in applying Generative AI and Large Language Model engineering concepts to business and technical use cases.
Ability to architect secure AI solutions within Microsoft 365 GCC High, Azure Government, and other regulated cloud environments.
Skilled in developing AI workflow automation using tools such as Power Platform, Copilot Studio, N8N, or equivalent platforms.
Ability to design and support personal AI assistant, agent, and workflow orchestration platforms.
Skilled in designing retrieval-augmented generation solutions, including embeddings, vector databases, and enterprise data retrieval systems (RAG, vector databases).
Ability to integrate AI and automation solutions with enterprise platforms such as ServiceNow, Salesforce, or equivalent SaaS applications.
Ability to apply secure software engineering practices to AI implementation, including compliance, governance, access control, and data protection considerations.
Skilled in interpreting and supporting federal compliance requirements, including CMMC, NIST SP 800-171, and DoD cybersecurity requirements.
Ability to lead Agile/Scrum delivery activities, including backlog management, sprint planning, prioritization, and stakeholder coordination.
Skilled in modern software engineering practices, including version control, CI/CD, code review, and infrastructure-as-code.
Ability to troubleshoot complex technical issues and develop practical, hands-on engineering solutions.
Ability to communicate technical concepts clearly to executive, technical, and non-technical audiences.
Ability to collaborate with cross-functional teams to drive enterprise adoption, change management, and continuous improvement.
Ability to manage multiple priorities in a fast-paced, secure, and compliance-driven environment.
Education and Experience
Bachelor's degree in Computer Science, Engineering, Data Science, or related field required. Master's degree in AI, Machine Learning, Computer Science, or related field preferred.
Minimum 6–12 years of experience in software engineering, AI/ML engineering, or related technical roles.
Demonstrated experience designing and deploying production-grade AI/ML or Generative AI systems.
Strong programming experience in Python and experience with APIs, backend systems, and integrations.
Experience working in Microsoft 365 GCC High or Azure Government environments.
Experience with Azure OpenAI, Copilot technologies, Power Platform, and Microsoft Graph.