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Maintain and operate a DevSecOps platform supporting secure software delivery. Build and troubleshoot CI/CD pipelines, automate builds/tests/security scans, manage infrastructure-as-code, integrate security gates, monitor pipeline health, manage artifacts and source control, and document operational procedures across AWS with some Azure support.

Lead design and delivery of production AI/ML services and MLOps infrastructure for defense missions. Define standards, architect automated pipelines and model-serving platforms, ensure monitoring, governance, security, and scalability, and mentor engineering and data science teams.

The Solutions Architect will design and implement cloud-based platforms, support architecture decisions, and collaborate with teams to deliver technical solutions for mission-critical systems.

Lead API strategy, architecture, and governance for a Department of War modernization effort. Define API standards, security patterns, gateway configuration, versioning, monitoring, and reusable integration patterns using Apigee/Gravitee. Guide implementation across cloud-native, microservices, and event-driven systems while mentoring engineers and ensuring alignment with DoW policies and security requirements.

Lead design and implementation of Databricks-based lakehouse and scalable data pipelines using Python, PySpark, SQL, and Delta Lake. Define engineering standards, ensure data quality, governance, CI/CD, and security, optimize Spark workloads across cloud platforms, and mentor engineers for mission-critical DoW analytics and AI/ML workloads.

Design and govern secure, scalable RESTful APIs and integration patterns for enterprise distributed systems. Develop API specifications (OpenAPI/Swagger/JSON Schema), manage API gateways (Apigee/Gravitee), create governance and lifecycle processes, collaborate with engineering and cybersecurity teams to enforce security controls, monitor API performance, and ensure alignment with DoW reference architectures and mission requirements.

Design, build, and maintain Databricks-based lakehouse data pipelines and products. Develop ETL/ELT (batch and streaming) using Python, PySpark, Spark, SQL, and Delta Lake; manage notebooks, jobs, clusters, and CI/CD; implement data quality, monitoring, lineage, governance, and security to support analytics and AI/ML for mission-critical defense workloads.

Design, build, and maintain production AI/ML services and MLOps pipelines for defense missions. Develop model training, validation, deployment, monitoring, and serving capabilities; ensure security, scalability, reproducibility, and governance. Collaborate with engineers, scientists, and cybersecurity teams to operationalize models and troubleshoot production systems.

Lead planning and delivery for a federal health data platform modernization effort. Coordinate across customers, partners, and technical teams; translate priorities into roadmaps, backlogs, milestones, and user stories; facilitate Agile ceremonies; manage scope, schedule, risks, dependencies, and reporting; support account management and business development activities.

Lead design and delivery of scalable production data pipelines and data products (Spark/Python/SQL) on Databricks; integrate diverse federal health systems, define reusable ingestion patterns, ensure data quality/governance, mentor engineers, and troubleshoot/optimize production workflows.

Support design and documentation of cloud and on-premises data solutions; translate mission needs into technical requirements; create architecture diagrams and technical materials; research technologies; participate in discovery and design discussions; collaborate with engineers to align implementations; communicate clearly to technical and nontechnical stakeholders while supporting a federal health data modernization mission.

Lead architecture for a federal health data modernization program, designing scalable hybrid-cloud data platforms, APIs, and integration patterns. Translate mission and security requirements into target-state architectures, guide legacy modernization, produce design artifacts, and collaborate with engineers, technical leads, and stakeholders to deliver secure, interoperable data products.

Design scalable hybrid/cloud data platform solutions for a federal health modernization initiative. Translate mission, data, security, and operational requirements into architectures, integration patterns, and documentation. Support Databricks and multicloud deployments, integrate legacy and modern systems via APIs and pipelines, collaborate with engineers and stakeholders, and enforce governance, security, and operational standards.

Design, build, and maintain scalable production data pipelines and APIs in a Databricks/Spark environment. Integrate and transform diverse health, financial, and operational datasets into reusable data products, implement data validation and governance, optimize pipeline performance, and collaborate with engineers, architects, and stakeholders to deliver reliable analytics datasets and platform capabilities.

Support implementation and maintenance of cybersecurity controls across cloud and platform environments for DoD missions. Perform RMF and ATO activities in eMASS, vulnerability scanning and remediation, incident response, security assessments, and documentation (SSPs, POA&Ms). Collaborate with engineers to integrate DevSecOps practices, secure containers and cloud-native apps, and maintain compliance with NIST/DoD frameworks.

Lead GCP operations and architecture for a mission-critical aviation platform. Provide day-two operational expertise, Tier 3 troubleshooting, Terraform and DevSecOps guidance, runbook and release-management support, and operational readiness improvements while working with Google advisors and customer teams to ensure platform reliability, resiliency, and secure near-real-time data exchange.

Design, implement, and maintain secure CI/CD pipelines, Infrastructure-as-Code (Terraform), and containerized cloud services. Integrate security throughout the SDLC, support deployment and operation of cloud-native data pipelines, manage vulnerabilities and secure configurations, implement cloud security controls and IAM, monitor system performance and compliance, and produce documentation and runbooks while collaborating with cross-functional teams in regulated environments.

Build and scale AI/ML-enabled features across frontend, backend, and data pipelines. Productionize ML models, deploy MLOps workflows, integrate inference APIs, optimize data models, ensure reliability, and collaborate with cross-functional teams for mission-critical analytics.

Design, build, and maintain secure, scalable cloud infrastructure and platform services (primarily in GCP) to support near real-time ingestion, processing, and analysis of high-volume time-series data. Implement containerized workloads, IaC (Terraform/Deployment Manager), CI/CD pipelines, cloud networking, IAM, and Zero-Trust controls. Troubleshoot production systems, collaborate with architects and stakeholders, produce documentation and runbooks, and ensure mission compliance in highly regulated environments.

Lead technical architecture and delivery of a Google Cloud-based, containerized, near real-time data platform. Design scalable, secure distributed systems, guide CI/CD and event-driven integrations, support engineering teams, produce architecture documentation, and liaise with mission stakeholders in a DoW environment requiring active clearance.