Artifical Intelligence (AI) Solution Architect
$180,000–$180,000 year
On-siteLincoln, Massachusetts, United States
Job Summary
Design and integrate AI and machine-learning services on the Mission Planning Enterprise platform to improve integration productivity, code assurance, and analytical insight for OEMs and engineering teams. Identify high-value use cases such as static and dynamic code analysis, automated test generation, anomaly detection, and intelligent defect triage. Govern the secure, explainable deployment of AI services on the DevSecOps/CDE stack with appropriate security, auditability, and model lifecycle management. Shape the roadmap for AI-enabled capabilities that support mission planning objectives, ensuring tight coupling with SOW-driven integration, evaluation, and cybersecurity needs. Work directly with engineering, IVV&E, and platform operations to deliver solutions that meet RMF and cyber policy requirements.
Required Qualifications
- Bachelor's degree in computer science, data science, or a related field
- 7+ years of experience architecting and delivering AI/ML‐enabled solutions, including at least 3 years in complex enterprise or regulated environments
- Strong understanding of software engineering and IVV&E workflows and how AI/ML can improve productivity and quality (e.g., code analysis, test selection, anomaly detection)
- Experience architecting AI services on modern platforms (containers, microservices, APIs) and integrating them with DevSecOps pipelines and tools
- Understanding of security, governance, and assurance considerations for AI, including data protection, model lifecycle management, and traceability of AI outputs
- An active Secret clearance or the ability to obtain one, and the ability to maintain it throughout employment
Desired Qualifications
- Experience applying AI/ML in defense, aerospace, or other mission‐critical software contexts (e.g., code assurance, cyber analytics, integration verification)
- Familiarity with mission planning software ecosystems and data structures, and an understanding of AI opportunities in integration, performance assessment, and deficiency analysis
- Background integrating AI‐driven analytics into program and technical performance dashboards to provide early indicators of risk
- Experience working closely with cybersecurity and ISSM teams to ensure AI solutions meet RMF and other cyber policy requirements
- Advanced degree in AI, machine learning, or a closely related discipline, and experience with MLOps practices in operational environments
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