Sr. Systems Engineer

Key Responsibilities

• Lead system architecture design for AI-driven applications and platforms, ensuring scalability, reliability, and security.
• Deploy, integrate, and optimize AI/ML models within enterprise and cloud environments (AWS, Azure, or GCP).
• Monitor performance, perform capacity planning, and enhance infrastructure for AI/ML workloads and data pipelines.Implement CI/CD pipelines, Infrastructure-as-Code (IaC), and container orchestration (Docker, Kubernetes).
• Ensure systems adhere to government security standards (e.g., NIST, FedRAMP, or state-specific frameworks).
• Partner with data scientists, software developers, and state IT stakeholders to ensure seamless AI system delivery and operation.
• Develop and maintain system diagrams, engineering documentation, and standard operating procedures for compliance and continuity.
• Provide Tier 3 technical support for system issues, incidents, and root cause analysis.
• Design and maintain secure sandbox and lower-tier environments that mirror production, enabling validation, testing, and phased rollout of AI and data services before public release.
• Implement FAIR-aligned data and system management practices ensuring that all deployed datasets and pipelines are Findable, Accessible, Interoperable, and Reusable across state and federal systems.
• Integrate Zero Trust security principles, continuous verification, and role-based access controls within all infrastructure layers, aligning with StateRAMP and NIST SP 800-53 controls.
• Automate compliance and security validation processes (e.g., configuration drift detection, encryption verification) to improve audit readiness and operational transparency.
• Collaborate with governance and data teams to ensure AI and synthetic data systems operate under approved privacy, security, and ethical-AI governance frameworks.
• Develop performance and compliance metrics (e.g., > 99.9 % system uptime, < 5 % unplanned downtime, 100 % encryption coverage) and report results through dashboards for MassTech oversight.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
• 8+ years of experience in systems engineering or infrastructure architecture roles.
• Strong understanding of AI/ML system integration, cloud platforms, and modern application environments.
• Hands-on experience with one or more cloud environments (AWS, Azure, or GCP).Proficiency in scripting and automation (Python, Bash, PowerShell, Terraform, or Ansible).
• Experience with CI/CD tools (Jenkins, GitLab CI, Azure DevOps, etc.).Solid grasp of network design, virtualization, and containerization technologies.Familiarity with government compliance frameworks (NIST, SOC 2, HIPAA, etc.).Demonstrated experience building and securing hybrid or multi-cloud environments aligned with Zero Trust and StateRAMP requirements.Proven ability to design systems supporting FAIR data management and WCAG 2.1 accessibility compliance.Experience implementing sandbox or staging environments that support phased deployment, validation, and governance testing for regulated AI workloads.US Citizenship or Permanent Residency required.Must reside in the Continental US.Depending on the government agency, specific requirements may include public trust background check or security clearance.

Preferred Qualifications

• Master’s degree in Systems Engineering, Computer Science, or a related field.Experience supporting state or federal government contracts.
• Exposure to AI/ML frameworks (TensorFlow, PyTorch, or similar).
• Knowledge of data governance, ethics, and AI policy as applied to public sector environments.
• Experience integrating observability, automated compliance validation, and audit logging into AI/ML operations pipelines.
• Familiarity with StateRAMP, NIST AI RMF, or equivalent frameworks, ensuring interoperability and security in AI-driven systems.
• Relevant certifications (AWS Certified Solutions Architect, Azure Solutions Architect, CISSP, or CompTIA Security+).