CFSA Solution Architect Lead D365 Power Platform Azure at Collaboredge Inc. — Washington, DC

Short Description:

CFSA requires a senior, hands-on Solution Architect resource to serve as the technical design authority for STAAND (Stronger Together Against Abuse and Neglect in DC), the District's federally certified Comprehensive Child Welfare Information System.

Complete Description:

CFSA requires a senior, deeply hands-on Solution Architect resource to serve as the technical design authority for STAAND (Stronger Together Against Abuse and Neglect in DC), the District's federally certified Comprehensive Child Welfare Information System (CCWIS).

STAAND is a person-centric, AI-enabled platform built on Microsoft Dynamics 365 and the Power Platform hosted in a Government Community Cloud (GCC) tenant, with Azure services operating in Microsoft's commercial cloud. It supports CFSA social workers, supervisors, private agency partners, providers, resource parents, and District sister agencies across nine functional modules — Intake and Investigations, Case Management, ICPC, Finance (Contracts, Service Logs, and Fiscal), Provider, Eligibility and Subsidy, Placement, Services, and Management Reports — plus six external portals (Mandated Reporter, MPD, NYTD, OSSE, Resource Parent, and Community). STAAND also fields CORA, an AI assistant supporting natural-language search and AI-assisted contact notes among other use cases.

The Resource will own architecture, security design, AI engineering, and the platform-release change cadence required to keep STAAND current and improving. This is a build-and-design role, not an advisory or oversight role. The Resource is expected to personally configure, code, prototype, review, and troubleshoot in the platform while serving as the credible technical voice to CFSA executive leadership, STAAND Product Team, OCTO, Microsoft, and Federal Partners (ACF/Children's Bureau).

The Resource will work under the direct supervision of the District DevOps Manager.

Scope of Work and Responsibilities

3.1 Solution and Platform Architecture

• Own and maintain the authoritative STAAND architecture: logical and physical data models, Dataverse table and relationship design, solution segmentation, environment strategy, and integration topology.
• Personally build in the platform — model-driven app configuration, plug-ins and custom APIs (C#/.NET), PCF controls, TypeScript/JavaScript client extensions, Power Fx, and plug-in pipeline optimization.
• Establish and enforce architecture standards, design patterns, naming conventions, and technical debt registers across all modules and portals.
• Chair design authority review for significant changes; sign off on solution designs before build.
• Diagnose deep platform issues: performance degradation, API and service-protection limits, plug-in execution ordering, solution layering conflicts, storage growth, portal rendering.
• Maintain architecture artifacts sufficient to satisfy CCWIS review, federal audit, and District IT governance.

3.2 Cross-Cloud Architecture: GCC and Commercial Azure

• Design, document, and harden the boundary between the GCC Dynamics/Power Platform tenant and Azure commercial-cloud services.
• Define what data may traverse that boundary, in what form (de-identified, tokenized, aggregated, or full record), under what authorization, and with what logging — including explicit architectural boundaries for protected data categories such as Medicaid Enrollment.
• Implement cross-tenant identity, managed identities, service principals, Key Vault secret lifecycle, private networking, and API gateway patterns.
• Maintain a defensible position on data residency and FedRAMP authorization boundaries for every commercial-cloud service in use, and present that position to auditors and federal reviewers.

3.3 AI and Agentic Development

• Serve as hands-on technical lead for CFSA's AI capability, including CORA and its expansion into agentic workflows.
• Design, build, evaluate, and productionize agents in Azure AI Foundry and Copilot Studio: tool and function calling, orchestration and multi-agent patterns, grounding and retrieval over Dataverse and document stores, prompt and context engineering, structured output, and human-in-the-loop checkpoints.
• Own AI evaluation discipline: golden datasets, automated evals, groundedness and hallucination measurement, regression testing on model or prompt changes, latency and cost benchmarking, controlled rollout.
• Manage the AI model lifecycle — track model releases and deprecations, run comparative evaluation before adopting a new model, execute migrations without regression to worker-facing quality.
• Implement responsible AI controls appropriate to a child welfare setting: content safety, PII/PHI handling, bias and fairness testing, explainability, audit logging of AI-influenced actions, and clear framing of AI output as decision support rather than decision making.
• Support predictive and analytic capability aligned to agency mission priorities, ensuring models are valida