• Define and evolve enterprise AI architecture patterns for LLM integration, retrieval-augmented generation, agentic workflows, prompt orchestration, and workflow automation. • Create reference architectures, design reviews, decision records, and implementation guidance that enable consistent AI development across business units. • Serve as a technical authority for AI platform decisions, including model selection, integration approaches, data boundary enforcement, and lifecycle management. • Evaluate emerging AI technologies and recommend fit-for-purpose adoption paths aligned to security, operational, and enterprise architecture requirements. • Partner with product, platform, and business technology teams to identify common needs and convert them into reusable engineering patterns. • Design and build reusable AI components such as connectors, agents, skill templates, prompt libraries, data pipelines, integration adapters, and service APIs. • Lead technical design for shared platform services for AI observability, logging, usage metering, evaluation, and lifecycle management. • Establish quality, versioning, deprecation, documentation, and contribution standards for the shared AI component catalog. • Guide teams through adoption of shared components, balancing standardization with practical implementation needs. • Identify opportunities to eliminate duplicate AI engineering efforts through consolidation, abstractions, and platformization. • Architect engineering controls for access management, data classification enforcement, prompt safety, output validation, audit logging, and policy adherence. • Partner with Security, Legal, and compliance stakeholders to embed responsible AI requirements into development and deployment pipelines. • Design model and agent lifecycle governance patterns, including version tracking, evaluation, drift monitoring, rollback, and deprecation workflows. • Build technical dashboards and telemetry that expose adoption, risk, performance, and governance compliance across AI-enabled systems. • Represent engineering considerations in AI governance reviews and translate policy requirements into implementable technical standards. • Develop AI-assisted workflow patterns that improve individual productivity, team collaboration, knowledge retrieval, meeting intelligence, document generation, and task automation. • Design measurement approaches that connect AI usage to time savings, quality improvement, error reduction, capacity creation, and business value. • Partner with Finance and platform teams to develop cost metering, showback/chargeback, and optimization mechanisms for AI services. • Mentor senior and mid-level engineers, raise engineering quality, and lead complex cross-functional technical initiatives from concept through production. • Contribute to communities of practice, internal enablement material, and technical evangelism for enterprise AI engineering standards.

• You will serve as a crucial link between applications, either custom development, COTS, or OSS, and the Navy platform environment, advocating best practices and facilitating communication between application teams and platform teams. • Evaluate and weigh different methods for solving complex technical problems; identify innovative solutions. • Solve technical problems that span 2-3 knowledge domains, showcasing a broad understanding of diverse technological landscapes. Demonstrate expert knowledge in 1-2 key technologies such as full-stack application development, CI/CD, GitOps, Kubernetes, Tofu, AWS, Go, or others, contributing to the team's technical excellence. • Contribute to the strategic planning that aligns technological advancements with the mission objectives. • Exhibit strong programming skills and deep familiarity with Linux/Unix operating systems. • Implement infrastructure as code and contribute to the build/maintenance of kubernetes clusters on various distributions (i.e EKS & RKE2). • Apply extensive experience with cloud native technology deployments, emphasizing secure coding practices and vulnerability remediation. • Build relationships with external teams and collaborate with other platform teams. • Travel Expectations: 4-12 times per year.

• Design, implement, and own infrastructure systems end-to-end, from initial design through to production operation. • Write high-quality, well-tested infrastructure code using Terraform, Helm charts, and CI/CD pipelines, actively contributing to team-wide standards. • Take ownership of complex production incidents—diagnosing, resolving, and driving blameless post-incident reviews to prevent recurrence. • Contribute to architectural discussions with well-reasoned proposals backed by practical experience. • Stay current with the cloud ecosystem and bring concrete, considered recommendations for tooling and approaches to the team. • Maintain a consistently high bar for scalability, resilience, and reliability across your areas of ownership. • Implement and improve observability using meaningful metrics, structured logging, and actionable alerting that surfaces real signals. • Ensure all infrastructure is version-controlled, reviewable, and reproducible, following infrastructure-as-code principles throughout. • Design and operate systems with security and compliance in mind—ensuring adherence to industry best practices and supporting audit requirements such as PCI-DSS and SOC 2. • Work closely with tech squads to help them consume platform capabilities effectively and unblock their delivery. • Partner with backend, data, and security engineers to align on shared infrastructure patterns and standards. • Communicate clearly about infrastructure changes, risks, and ongoing work to the teams that depend on the platform.

Role Description We are looking for a Platform Software Engineer, DevOps Engineer, or similar roles with the following qualifications: - 5+ years of professional experience in relevant roles. - Advanced English is required. - Successful completion of a four-year college degree is required. - Extensive experience deploying and operating containerized applications using Kubernetes. - Hands-on experience building deployment automation and managing service lifecycles in Kubernetes environments. - Proven experience working with self-hosted open-source platforms and internet-facing services. - Strong background in DNS architecture, authoritative DNS servers, zone delegation, and domain management. - Demonstrated experience configuring email infrastructure, SMTP, mail routing, and email authentication technologies such as SPF, DKIM, and DMARC. - Practical experience developing web scraping, content generation, or data transformation pipelines. - Solid understanding of REST APIs, service orchestration, and distributed systems. - Hands-on experience implementing infrastructure monitoring and observability using Grafana, Prometheus, or similar platforms. - Knowledgeable in cloud platforms such as AWS, Azure, or Google Cloud Platform. - Familiar with CI/CD pipelines and infrastructure automation. - Demonstrated experience building scalable backend services using modern programming languages such as Go, Python, Java, or similar. - Practical experience working with Linux systems, networking, and containerized workloads. - Solid understanding of PKI, TLS certificates, and secure communication protocols. - Experience with cybersecurity, red team infrastructure, cyber ranges, or security simulation platforms is highly desirable. - Ability to work through new and difficult issues and contribute to libraries as needed. - Ability to create and maintain continuous integration and delivery of applications. - Forensic attention to detail. - A positive mindset and a can-do attitude. - Experience working on Agile/Scrum teams. - Meaningful experience working on large, complex systems. - Ability to take extreme ownership over your work. - Ability to identify with the goals of FullStack's clients and dedicate yourself to delivering on the commitments you and your team make to them. Qualifications - 5+ years of professional experience in relevant roles. - Advanced English is required. - Successful completion of a four-year college degree is required. Requirements - Extensive experience deploying and operating containerized applications using Kubernetes. - Hands-on experience building deployment automation and managing service lifecycles in Kubernetes environments. - Proven experience working with self-hosted open-source platforms and internet-facing services. - Strong background in DNS architecture, authoritative DNS servers, zone delegation, and domain management. - Demonstrated experience configuring email infrastructure, SMTP, mail routing, and email authentication technologies such as SPF, DKIM, and DMARC. - Practical experience developing web scraping, content generation, or data transformation pipelines. - Solid understanding of REST APIs, service orchestration, and distributed systems. - Hands-on experience implementing infrastructure monitoring and observability using Grafana, Prometheus, or similar platforms. - Knowledgeable in cloud platforms such as AWS, Azure, or Google Cloud Platform. - Familiar with CI/CD pipelines and infrastructure automation. - Demonstrated experience building scalable backend services using modern programming languages such as Go, Python, Java, or similar. - Practical experience working with Linux systems, networking, and containerized workloads. - Solid understanding of PKI, TLS certificates, and secure communication protocols. - Experience with cybersecurity, red team infrastructure, cyber ranges, or security simulation platforms is highly desirable. - Ability to work through new and difficult issues and contribute to libraries as needed. - Ability to create and maintain continuous integration and delivery of applications. - Forensic attention to detail. - A positive mindset and a can-do attitude. - Experience working on Agile/Scrum teams. - Meaningful experience working on large, complex systems. - Ability to take extreme ownership over your work. - Ability to identify with the goals of FullStack's clients and dedicate yourself to delivering on the commitments you and your team make to them. Benefits - Competitive pay. - 100% remote work. - The ability to work with leading startups and Fortune 500 companies. - Continuing education opportunities. - Opportunity to grow and expand your career.