AI Solutions Architect - Remote

The AI Solutions Architect is responsible for partnering with business units across the organization to identify operational bottlenecks, evaluate automation and AI opportunities, and architect solutions that drive measurable efficiency gains across multiple service lines. This role combines deep technical expertise in AI, data engineering, and platform architecture with strong business acumen and stakeholder engagement skills. The AI Solutions Architect works closely with business unit leaders, engineering teams, and executive stakeholders to evaluate build vs. buy decisions, ensure cross-functional alignment, and deliver scalable solutions that serve multiple teams rather than siloed, one-off implementations. Key Responsibilities Business Unit Partnership and Solutioning • Meet regularly with business unit leaders to understand operational pain points, inefficiencies, and automation opportunities • Translate business problems into technical solution designs that leverage AI, automation, and modern platform capabilities • Facilitate cross-functional alignment to ensure solutions serve multiple business units and avoid duplicative efforts. AI and Automation Strategy • Evaluate and recommend AI/ML tools, platforms, and frameworks that align with enterprise objectives and security requirements • Develop and maintain a solutions roadmap that ties automation initiatives to measurable business outcomes such as efficiency gains and EBITDA impact • Stay current on emerging AI capabilities and assess their applicability to organizational challenges. Architecture and Platform Design • Design scalable, secure architectures for AI and automation solutions across cloud and hybrid environments • Define technical standards, integration patterns, and data pipeline architectures that support repeatable, cross-functional solution delivery • Ensure all solutions align with enterprise security posture, regulatory obligations, and compliance frameworks including CMMC, NIST, and DFARS. Build vs. Buy Evaluation • Lead objective assessments of commercial platforms versus custom-built solutions, considering cost, scalability, security, and long-term maintainability • Develop business cases and technical recommendations for executive review • Manage vendor evaluation processes and proof-of-concept efforts where applicable. Data Strategy and Engineering • Oversee data infrastructure design, including pipelines, storage, and integration layers that support AI and automation workloads • Ensure data quality, governance, and accessibility standards are maintained across solutions • Partner with engineering teams to implement and optimize data flows that feed AI models and automation tools. Security and Compliance Integration • Ensure all AI and automation solutions are designed with security-first principles, including secure data handling, access controls, and threat modeling • Evaluate the security posture of third-party AI platforms and tools prior to adoption, ensuring alignment with organizational security standards • Collaborate with cloud security and compliance teams to ensure solutions meet CMMC, NIST SP 800 series, DFARS, ITAR, and other applicable regulatory requirements • Define and enforce security guardrails for AI model deployment, data ingestion, and API integrations across all solution architectures • Support internal and external security assessments by providing architectural documentation and evidence of control implementation. Stakeholder Engagement and Reporting • Provide regular updates to executive leadership on solution progress, business impact, and roadmap status • Document solution designs, architectural decisions, and technical standards for organizational transparency and audit readiness • Champion a culture of AI adoption and operational efficiency across the organization Qualifications US Citizenship Required Must possess, and be able to maintain a Secret Clearance. Minimum Qualifications • Bachelor's degree in Computer Science, Data Science, Engineering, or a related discipline. • A minimum of five years of progressive experience in solutions architecture, data engineering, AI/ML engineering, or a combination of related technical disciplines. • Demonstrated experience designing and delivering AI or automation solutions in enterprise environments. • Proven ability to engage with non-technical business stakeholders, translate operational challenges into technical solutions, and drive cross-functional alignment. • Strong experience with cloud platforms (Azure, AWS, or GCP), data pipeline technologies, and modern AI/ML frameworks. • Experience operating in regulated environments with familiarity with compliance frameworks such as CMMC, NIST SP 800 series, DFARS, or equivalent. Preferred Qualifications • Eight or more years of experience across solutions architecture, data engineering, and AI/ML. • Experience in the government contracting or defense sector. • Hands-on experience with large language