• Design and implement secure, scalable AWS infrastructure solutions using tools such as Terraform and CloudFormation • Refactor organization-wide environments, standardizing multi-account landing zones, unified IAM models, and automated compliance guardrails aligned with CIS benchmarks • Standardize core cloud networking, including DNS management, traffic segmentation, routing patterns, and secure cross-cloud/intra-cloud connectivity • Manage containerized applications using Docker and Kubernetes/EKS, ensuring optimal performance, scalability, and zero-trust network policies • Develop and optimize end-to-end deployment pipelines (GitHub Actions, GitLab CI, Jenkins) and create custom automation scripts using Python, Bash, or Go • Implement and maintain robust logging, monitoring, and alerting systems (CloudWatch, Prometheus, VictoriaMetrics, ELK) to enhance operational readiness and reduce downtime

Role Description Advance your career while shaping the future of cloud operations that support GDIT enterprise environments. Step into the role of Azure Cloud Engineer at GDIT, where technologists are empowered to grow meaningful careers while continually evolving their skills. As an Azure Cloud Engineer, the work you do at GDIT directly strengthens the reliability, security, and scalability of GDIT’s cloud ecosystem. In this role, you will play a pivotal part in ensuring our operations are supported by resilient, high‑performing Azure and Oracle cloud services, enabling rapid delivery, secure operations, and continuous modernization. - Support Azure‑focused cloud engineering initiatives, ensuring stable, secure, and compliant cloud operations that directly enable organizational mission success. - Collaborate with cross‑functional teams including cybersecurity, application, and infrastructure partners to ensure cloud platforms align with mission and operational requirements. - Drive innovation in automation, cloud optimization, and operational efficiency to enhance service delivery, reduce downtime, and quickly resolve mission-impacting challenges. - Utilize advanced cloud engineering tools and technologies such as Azure CLI, PowerShell, IaC frameworks, Kubernetes, Oracle Cloud services, and supporting AWS capabilities to modernize and sustain the cloud environment. Qualifications - Education: Bachelor’s degree NOT required. An additional 4 years of equivalent experience OR an Azure Certification may substitute. - Experience: 8+ years of IT engineering experience, 12+ in lieu of no degree. - 5+ years hands-on experience managing Azure cloud operations. - Strong understanding of cloud architecture, security, and automation. - Experience with PowerShell, Python, JSON, YAML, Git, and cloud-native CLIs. - Experience working with serverless, Docker, and Kubernetes. - Windows and Linux OS experience. - Demonstrated experience with Oracle Gov Cloud Infrastructure (OCI), and AWS Gov infrastructure experience/certification preferred. - US Person required. - Excellent communication and documentation skills. - Ability to work in an on-call rotation as required. Benefits - AI-powered career tool that identifies career steps and learning opportunities. - An internal mobility team focused on helping you achieve your career goals. - Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off. - Full-flex work week to own your priorities at work and at home. - Award-winning culture of innovation and a military-friendly workplace. Company Description We are GDIT. A global technology and professional services company that delivers consulting, technology and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50 countries worldwide, offering leading capabilities in digital modernization, AI/ML, Cloud, Cyber and application development. Together with our clients, we strive to create a safer, smarter world by harnessing the power of deep expertise and advanced technology.

Role Description We are hiring a Junior / Mid-Level Full-Stack Platform Engineer for a fast-moving biometric health technology company building production systems around wearable physiological data, APIs, SDKs, and AI-forward infrastructure. This is a hands-on builder role for someone early in their engineering career who already has real full-stack experience and strong fundamentals. - Build and improve full-stack platform features across frontend, backend, APIs, SDKs, and data systems. - Write Python- or Go-backed services and work with JavaScript or TypeScript on product-facing surfaces. - Support data pipelines and platform workflows that connect biometric data, enterprise systems, and AI-facing infrastructure. - Collaborate with senior engineers on architecture, implementation, deployment, and technical tradeoffs. - Ship clean, reliable code in a compliance-aware environment. - Debug production-adjacent issues, reason through data flow, and improve the platform over time. - Move quickly without waiting for every detail to be prescribed. Qualifications - Hands-on full-stack software engineering experience from a professional role, internship, startup, open-source work, or substantial shipped project. - Strong Python or Go skills. - Experience building backend services, APIs, SDKs, or data pipelines. - Practical frontend experience, especially JavaScript or TypeScript. - Solid fundamentals in Git, testing, debugging, deployment, interfaces, and data flow. - Comfort working in a lean startup where priorities move quickly. - Ability to communicate tradeoffs clearly and learn from senior engineers. - Willingness to complete a live coding assessment. - Recent grads can be a fit when they have unusually strong full-stack project, internship, startup, or open-source evidence. Requirements - Depth across both Python and Go. - AI/ML, AI tooling, data infrastructure, or model-facing platform exposure. - Health tech, wearables, biometric data, IoT, or device-connected software experience. - HIPAA, SOC 2, GDPR, or other compliance-aware engineering experience. - Austin, San Antonio, or broader Texas location. - Strong science, engineering, computer science, or systems-oriented background. Benefits - Real platform work in biometric health technology, not toy internal tools. - Direct exposure to AI-forward infrastructure, data pipelines, APIs, and SDKs. - Mentorship from senior technical leaders while still owning meaningful build work. - A lean startup environment where strong early-career engineers can grow quickly. - Remote/distributed setup, with Austin / San Antonio preferred but not required. - $90,000-$130,000 base salary for the right early-career or junior/mid-level profile, with additional flexibility for exceptional profiles. Company Description This is a full-time role with a distributed U.S. team. Austin / San Antonio is preferred, but the engineering team is already distributed, so location is helpful rather than mandatory. The posted salary range is $90,000-$130,000 base salary, with additional flexibility for exceptional profiles. Final compensation depends on experience, skill level, technical assessment performance, and fit for the role.

• Define and drive the technical roadmap for platform infrastructure, reliability, and scalability initiatives. • Design and review complex system architectures that support company growth and evolving business needs. • Establish engineering standards, best practices, and technical patterns across multiple teams. • Improve system observability, incident response processes, and operational excellence across the platform. • Partner with Engineering, Product, and Design leaders to align technical investments with business priorities. • Mentor engineers and provide technical guidance that elevates engineering capabilities across the organization. • Build and improve backend services, infrastructure tooling, and shared platform capabilities. • Identify technical debt, scalability risks, and operational vulnerabilities before they become business constraints.