SummaryOwn the target-state and transition architecture for modernized Medicaid DDI and Provider Plus capabilities. Set architecture direction and AI-enabled engineering guardrails across applications, data, integrations, cloud, security, platform delivery and operations, balancing client commitments, scalability, risk, cost and maintainability.
Your role in our missionProfessional CapabilitiesArchitecture governance, roadmaps, cost optimization and executive communication.Leadership across product, delivery, client and vendor stakeholders.
What we're looking for12 or more years in application architecture or product engineering.Architecture leadership for complex enterprise, SaaS or cloud-native platforms across the full SDLC.Deep experience with applications, APIs, integrations, data, security, DevSecOps, reliability and modernization.Medicaid, Medicare, MMIS/MES or highly regulated industry experience preferred.
Modernized DDI Technical Skills- Application architecture: React/TypeScript, .NET 10/ASP.NET Core, microservices, serverless, DDD, distributed systems and API lifecycle.
- Cloud and data: AWS Lambda, API Gateway, S3, SQS, Glue/Spark, MSK/Kafka, EKS, PostgreSQL, canonical models and reconciliation.
- Platform and reliability: Terraform, containers, Git, CI/CD, OpenTelemetry, SRE, high availability, disaster recovery, SLAs and SLOs.
- Security architecture: OIDC/OAuth, SSO, MFA, RBAC, secrets, encryption, tenant isolation, zero trust and HIPAA, PHI/PII protection, OWASP, Section 508/WCAG, secure SDLC and DevSecOps.
- Modernization: Multi-tenant SaaS, multi-version support, adapter/strangler patterns, functional parity and production adoption.
AI-Driven Delivery Skills- Define enterprise guardrails for approved AI development tools, including GitHub Copilot, Codex or comparable platforms, covering permitted use, data boundaries, review and evidence requirements.
- Architect AI-assisted software-delivery patterns for code generation, test generation, specification-to-code workflows, legacy analysis and modernization, without bypassing SDLC controls.
- Evaluate AI-generated designs and code for architecture alignment, security, quality, performance, maintainability, licensing/provenance and operational risk.
- Define human-in-the-loop controls, traceability, evaluation criteria, quality gates and escalation paths for AI-assisted engineering decisions.
- Use blended AI-driven analysis to synthesize requirements, architecture dependencies, release impacts and modernization options while validating conclusions against authoritative sources.
- Assess AI tool/vendor fit, integration, identity, privacy, auditability, cost and lifecycle risk; communicate recommendations to governance and executive stakeholders.
What you should expect in this roleThe pay range for this position is $118,800.00 - $169,700.00 per year, however, the base pay offered may vary depending on geographic region, internal equity, job-related knowledge, skills, and experience among other factors. Put your passion to work at Gainwell. You'll have the opportunity to grow your career in a company that values work flexibility, learning, and career development. All salaried, full-time candidates are eligible for our generous, flexible vacation policy, a 401(k) employer match, comprehensive health benefits, and educational assistance. We also have a variety of leadership and technical development academies to help build your skills and capabilities.
