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Develop and maintain secure, scalable full-stack applications for federal healthcare programs. Responsibilities include front-end, back-end, API, and database development; AWS deployment and support; CI/CD pipeline automation; infrastructure-as-code contributions; monitoring and troubleshooting; vulnerability remediation; and secure DevSecOps practices throughout the software development lifecycle.

Lead technical execution and solution architecture for cloud-based federal health software programs. Guide developers, translate requirements into implementation direction, manage technical risks, document architecture decisions, and ensure secure, scalable, maintainable solutions across application, API, and data layers. Partner with QA and DevSecOps teams on testing, CI/CD, infrastructure-as-code, security, and releases. Provide mentoring, technical reviews, hands-on engineering support, and occasional proposal or innovation assistance.

Designs, develops, tests, deploys, and supports secure, scalable full-stack applications for federal healthcare programs. Responsibilities span front-end, back-end, APIs, databases, AWS cloud services, CI/CD pipelines, infrastructure as code, monitoring, troubleshooting, vulnerability remediation, and production support. The role collaborates with product, architecture, infrastructure, analytics, and platform teams while meeting CMS security, privacy, and DevSecOps requirements.

Designs, develops, delivers, tests, maintains, and improves computer-based training and eLearning for federal healthcare programs. Creates Storyline 360 modules, simulations, scripts, assessments, accessibility-compliant materials, presentations, and training documentation. Collaborates with SMEs, stakeholders, product teams, and end users to translate complex technical information into learner-centered content. Manages LMS course delivery and tracking, conducts peer reviews, facilitates feedback sessions, and evaluates training effectiveness.

Owns the requirements lifecycle from stakeholder intake through implementation and acceptance. Translates business needs into technical requirements, user stories, process flows, acceptance criteria, and SDLC documentation. Manages product backlog and release planning, facilitates stakeholder sessions, supports testing and production releases, investigates issues using SQL and data mappings, and contributes to reporting, troubleshooting, and post-implementation analysis.

Design, build, and optimize scalable AWS and Snowflake data pipelines, databases, data models, and cloud-based solutions. Implement ETL/ELT workflows, data quality and monitoring frameworks, CI/CD pipelines, automated recovery, documentation, and performance improvements. Collaborate with stakeholders and cross-functional teams in an Agile environment while conducting advanced analysis using Python and SQL.

Serves as the primary contact for Medicaid agencies during data request and attestation processes. Provides technical assistance, drafts responses, facilitates stakeholder meetings, validates submissions, communicates findings, and maintains project documentation and systems. Supports program administration, client updates, and requirements definition for CMS data-sharing initiatives.

Develop and productionize machine learning, deep learning, NLP, RAG, LLM, and knowledge graph solutions for federal healthcare clients. Build AWS-based ML pipelines, perform statistical modeling and data analysis, create visualizations, evaluate models, and communicate insights. Collaborate with cross-functional Agile teams to deliver AI strategies aligned with CMS and healthcare policy objectives.

Designs, builds, and optimizes scalable AWS and Snowflake data pipelines, infrastructure, data models, semantic layers, and data quality frameworks. Analyzes Medicare, Medicaid, and CMS repository data to support analytics and reporting. Responsibilities include workflow monitoring, automation, governance, security, performance optimization, stakeholder collaboration, and Agile delivery using modern DevOps and software engineering practices.

Leads advanced data science and AI initiatives addressing healthcare and Medicaid/CHIP policy challenges. Develops and deploys machine learning, NLP, LLM, RAG, predictive modeling, and knowledge graph solutions on AWS. Establishes MLOps, monitoring, evaluation, and responsible AI practices; mentors data scientists; evaluates emerging technologies; creates visualizations and dashboards; and collaborates with federal healthcare stakeholders to deliver scalable, data-driven products.