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AI Practice Lead

Job in Reston, Fairfax County, Virginia, 22090, USA
Listing for: Riva Solutions Inc
Full Time position
Listed on 2026-09-28
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 190000 - 200000 USD Yearly USD 190000.00 200000.00 YEAR
Job Description & How to Apply Below

RESULTS. INNOVATION. VALUES. ACCOUNTABILITY.

That’s RIVA.

We’re a mission-driven IT services company and systems integrator supporting digital transformation and modernization for federal government agencies. Since 2009, we’ve partnered with our customers to solve complex challenges through smart, practical innovation to deliver real outcomes where they matter most. Our teams are made up of industry-leading experts who are passionate about doing great work and making a difference. We don’t just develop solutions, we support efforts that strengthen communities and serve the public good.

RIVA’s culture is built on four core values:
Results, Innovation, Values, and Accountability. They guide how we work, how we collaborate, and how we measure success. Our employee-first approach is rooted in trust, ownership, and meaningful work. By investing in our people and fostering a flexible, supportive environment, employees have the opportunity to grow their skills, contribute ideas, and make an impact from day one. all while supporting missions that matter.

POSITION

OVERVIEW

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.

CORE 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)…
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