AI Practice Lead

About the role

RIVA is seeking an innovative and hands-on AI Practice Lead to architect, advance, and scale our next-generation AI capabilities across our core business lines. This strategic and highly visible role combines thought leadership with the technical depth to prototype, design, and deploy cutting-edge AI solutions that deliver measurable impact to both internal operations and federal customers. The AI Practice Lead will work closely with the CTO, technical delivery teams, and business development organization to drive RIVA’s AI roadmap — building reusable frameworks, establishing governance, and ensuring responsible and secure AI integration across programs. The ideal candidate brings deep expertise in AI/ML system design, modern cloud architectures, and leadership experience in shaping enterprise-wide AI strategy.

Responsibilities

• Define and lead the roadmap for RIVA’s AI Practice, ensuring alignment with company strategy and customer mission outcomes.
• Architect and deliver end-to-end AI solutions, including data ingestion, model design, training/tuning, deployment, and lifecycle governance.
• Build and scale AI/ML operations (MLOps) pipelines with automation, monitoring, and version control best practices.
• Serve as a hands-on technical expert, designing proofs of concept (POCs) and implementing AI system components as needed.
• Partner with cross-functional teams to design scalable, secure, and cloud-native AI solutions using AWS and Microsoft Azure AI/ML services.
• Collaborate with BD/Sales teams to develop AI-enabled proposals, build demonstrations, and engage with customers during pre-sales activities.
• Establish and promote AI delivery standards, frameworks, and governance models emphasizing ethical and responsible AI use.
• Integrate cybersecurity, compliance, and data privacy standards into AI architectures.
• Track and evaluate emerging AI trends to identify new capabilities for adoption within RIVA’s delivery teams.
• Mentor and grow a multi-disciplinary AI team of engineers, data scientists, and designers.
• Define and monitor KPIs to measure AI adoption, customer success, and delivery quality across projects.

Minimum Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Development, Engineering, or a related field.
• 10+ years of experience delivering AI/ML-based solutions, including at least 5 years in an architecture or technical leadership capacity.
• Proven hands-on experience building AI prototypes, ML models, and production-grade pipelines.
• Strong experience with AWS and Microsoft Azure AI/ML services and cloud-native data architectures.
• Expertise in machine learning (ML), deep learning (DL), and large language model (LLM) deployment and governance.
• Familiarity with MLOps practices, continuous integration, and model lifecycle management.
• Experience applying human-centered design principles to AI-driven solutions.
• Knowledge of cybersecurity and data compliance considerations in AI environments.
• Strong collaboration skills and ability to interface with both technical and executive stakeholders.
• Excellent written and verbal communication skills.
• U.S. Citizenship and the ability to obtain a Federal Security Clearance.

Preferred Qualifications

• Advanced degree in Artificial Intelligence, Machine Learning, or Software Development.
• Experience deploying Generative AI (GenAI) or LLM-based solutions in enterprise or federal environments.
• Background building or scaling AI practices, Centers of Excellence (CoEs), or reusable AI frameworks.
• Proficiency with Infrastructure as Code (IaC), containerization, and scalable microservice architectures.
• Familiarity with low-code/no-code AI platforms or workflow automation tools.

The salary or salary range for this role reflects an estimated range informed by multiple compensation factors. Final offers may vary based on considerations such as relevant experience, education and training, critical skillsets, and overall business needs.