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Leads architecture, scaling, governance, and implementation of enterprise data platforms across multi-cloud and air-gapped environments. Designs batch and streaming systems, optimizes Spark and Trino/Presto clusters, implements Terraform-based infrastructure, establishes data quality, lineage, security, and compliance controls, and leads Agile engineering pods while mentoring staff. Requires advanced expertise in distributed data systems, cloud platforms, Kubernetes, programming, and regulated defense environments.

Designs, builds, and integrates AI/ML solutions and microservices for defense and intelligence missions. Responsibilities include fine-tuning language models, developing RAG pipelines and vector search integrations, designing model training and data pipelines, deploying containerized services with Docker and Kubernetes, integrating security scanning into CI/CD, managing multi-cloud environments, and mentoring developers in Agile teams.

Leads architecture and implementation of enterprise AI applications and agentic LLM workflows. Optimizes model inference, memory usage, quantization, and deployment for air-gapped environments. Designs multi-cloud Kubernetes infrastructure with Terraform, establishes DevSecOps security scanning and remediation, and drives Agile execution, technical debt management, and team mentorship.

Supports the development, testing, and deployment of AI and machine learning pipelines in secure environments. Responsibilities include maintaining ML data ingestion workflows, writing Python and Bash code, containerizing applications with Docker, conducting unit tests and security scans, and participating in Agile ceremonies, code reviews, and backlog refinement.

Supports CI/CD pipeline operations using Jenkins and GitLab CI/CD, integrates security scanning and automated testing, assists with vulnerability remediation, and maintains security compliance. Works with senior engineers to learn Infrastructure-as-Code and DevSecOps practices. Requires foundational experience with scripting, Linux administration, version control, containers, infrastructure automation, networking, and CI/CD concepts.

Architects and leads enterprise-scale AI software systems, including novel AI frameworks, LLMs, MLOps, multi-cloud and air-gapped infrastructure. Serves as the technical authority for high-assurance machine learning, container security, DevSecOps, and enterprise architecture. Advises government and agency leadership, establishes security standards, leads vulnerability remediation, and aligns engineering roadmaps with mission objectives.

Manage and extend enterprise cloud services and environments, implement DevSecOps and security-first architectures (IAM, encryption, segmentation), develop tools to assess cyber vulnerabilities, support integration/deployment of Manticore and Kraken, and improve architecture to protect Space Force networks.

Design, deploy, and maintain cloud infrastructure and Kubernetes platform services to ensure availability, scalability, security, and CI/CD automation. Implement IaC (Terraform), DevSecOps pipelines, monitoring, and DISA STIG hardening while collaborating with cross-functional teams on Platform One/Cloud One mission applications.

The Data Engineer/ETL Engineer will support cloud-based and on-prem application development, focusing on data management and analytics for defense and intelligence.

Design, build, and optimize high-throughput data pipelines and infrastructure for Defense Health. Develop RESTful APIs and cloud data solutions (AWS), apply DevSecOps and TDD, use Python, Trino, Spark, dbt, and Rancher Kubernetes, and collaborate with stakeholders to deliver secure, production-grade analytics services.