Sr. Solutions Architect

Key Responsibilities

• Lead the end-to-end architecture of AI, analytics, and automation solutions supporting state government missions.
• Define technical roadmaps and solution blueprints for AI/ML platforms, natural language processing (NLP), predictive analytics, and generative AI capabilities.
• Ensure architecture aligns with state IT enterprise frameworks, security policies, and data governance requirements.
• Partner with the program director, technical teams, stakeholders to translate business goals into scalable, implementable technical designs.
• Present solution architectures, proof-of-concept results, and technical documentation to non-technical audiences and oversight committees.
• Provide hands-on guidance to data scientists, developers, and system engineers during system design and deployment.
• Evaluate and recommend AI tools, platforms, and frameworks (e.g., Azure AI, AWS SageMaker, Google Vertex AI, OpenAI, Databricks, Snowflake).
• Define integration strategies for AI solutions within legacy systems and statewide data ecosystems.
• Design solutions compliant with state and federal data privacy standards (HIPAA, CJIS, GDPR, etc.).Architect FAIR-compliant (Findable, Accessible, Interoperable, Reusable) data frameworks ensuring metadata consistency and interoperability across CKAN, Dataverse, and other state systems.
• Integrate synthetic-data generation pipelines and AI fairness frameworks (AIF360, Fairlearn) to support privacy-preserving innovation and bias mitigation
• Apply Zero Trust security principles and role-based access controls (RBAC) throughout the architecture to protect controlled and restricted datasets.
• Embed accessibility and inclusivity requirements (WCAG 2.1 Level AA and multilingual readiness) into user-facing and developer interfaces.
• Lead architecture validation in sandbox environments, ensuring each phase of deployment meets MassTech’s governance checkpoints and audit requirements.
• Deliver metrics-driven outcomes (e.g., ≥99.9 % uptime target, ≥95 % security control coverage, 100 % metadata validation compliance) to demonstrate platform performance and accountability.
• Ensure adherence to AI governance and ethical AI practices, including transparency, fairness, and explainability.
• Lead architecture reviews, milestone presentations, and risk assessments throughout project lifecycles.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 8+ years of IT architecture experience, including 5+ years in cloud and data solution design.
• Demonstrated experience architecting AI/ML solutions in enterprise or government environments.
• Expertise with at least one major cloud platform (AWS, Azure, GCP) and their AI services.
• Strong knowledge of data architecture, API integration, model deployment, and MLOps pipelines.
• Familiarity with state or federal IT procurement and compliance frameworks.
• Demonstrated experience architecting FAIR-aligned data platforms and secure metadata pipelines for AI or data-commons initiatives.
• Knowledge of synthetic-data generation frameworks (e.g., SDV, Synthea) and their application in privacy-preserving model training and testing.
• Working knowledge of accessibility compliance (Section 508 and WCAG 2.1 AA) and inclusive design principles for data and AI systems.
• Excellent communication and documentation skills for executive and technical audiences.
• 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 a relevant technical field.
• Experience with AI ethics, governance frameworks, and model interpretability.
• Certifications: AWS Solutions Architect – Professional, Azure Solutions Architect Expert, or equivalent.
• Prior experience supporting state or local government contracts or modernization initiatives.
• Understanding of Zero Trust, NIST AI Risk Management Framework, and data fabric architectures.
• Experience designing or implementing data commons or metadata-driven catalog solutions (e.g., CKAN, Dataverse) for research or government programs.
• Proven track record applying FAIR principles, AI ethics frameworks, and sustainability metrics to large-scale AI/ML deployments.