Role Description As a remote Senior Information Assurance (IA) Engineer, you will lead critical cloud security operations, DevSecOps pipeline integration, and compliance auditing. The ideal candidate will have extensive hands-on experience securing AWS cloud infrastructure operating at DoD Impact Level 5 (IL5), with preparations for Impact Level 6 (IL6). This senior role requires deep expertise in Application Security (AppSec) tools, secure code methodologies, and vulnerability management, along with a foundational understanding of the DoD Risk Management Framework (RMF) to support continuous compliance and Authority to Operate (ATO) efforts. Responsibilities - Lead the design, implementation, and maintenance of advanced security controls within AWS cloud environments operating at DoD IL5, ensuring architectural readiness for future IL6 integration. - Architect and manage security testing integrations within Azure DevOps (ADO) and Git environments. Embed and automate Application Security (AppSec) into the CI/CD pipeline. - Administer, utilize, and optimize security testing tools, specifically Fortify and Tenable, to identify, assess, and drive the remediation of code and infrastructure vulnerabilities. - Conduct continuous compliance auditing and security assessments. Apply foundational (junior-level) knowledge of the DoD Risk Management Framework (RMF) to support the generation and maintenance of artifacts required for Authority to Operate (ATO). - Analyze complex security scan results, coordinate cross-functionally with development teams to remediate findings, and enforce strict DoD security configuration guidelines (e.g., STIGs, SRGs). - Provide input to internal project teams consisting of both contract partners and government customers to ensure effective use of IT solutions, tools, and processes. Qualifications - MA/MS in a related field with a minimum of 10+ years of relevant experience, or BA/BS in a related field with a minimum of 15+ years of relevant experience. - Five years’ experience in monitoring, testing, troubleshooting, and performing corrective actions for Cybersecurity IT systems. - Active Secret security clearance. - U.S. citizenship required. - CompTIA Security+ Certification. - Direct operational experience with security scanning and vulnerability management tools, specifically Fortify and Amazon Inspector. - Proficiency with Git and CI/CD orchestration using Azure DevOps (ADO). - Demonstrates foundational knowledge of the RMF lifecycle, ATO processes, and DoD security methodologies. - Practical understanding of key technologies including defensive cyber event logging, application security, commercial DoD PKI, and AWS/Azure cloud authorization. - Experience in developing metrics from associated Cybersecurity elements, including trend analysis. - Ability to provide input to internal project teams consisting of both system users and IT resources as well as functional proponents and Army communities. Preferred Qualifications - Prior experience working with ECMA to implement DoD cloud solutions. - Familiarity with additional code quality and security tools such as SonarQube, Semgrep, or Checkmarx. - Prior experience transitioning enterprise systems from DoD IL5 to IL6 environments. - Advanced cloud or security certifications (e.g., AWS Certified Security Specialty, CISSP, CCSP). Benefits - A competitive compensation package. - Comprehensive health and wellness benefits, including medical, dental, and vision plans. - Access to company-provided retirement savings options with matching contributions. - Opportunities for professional growth and continued learning. - Additional perks such as discounts on various services and products. - Remote work.

Senior Full-Stack Engineer (AI-Enabled) Location: Remote in Georgia Job Description: JavaScript (Fullstack) FacebookLinkedInSend via email Looking for something else? Find a vacancy that works for you. Send us your CV to receive a personalized offer. We are seeking a Senior Full-Stack Engineer with strong hands-on experience in modern web development and practical exposure to AI technologies. You will build scalable applications and contribute to integrating AI-driven features into production systems. Responsibilities - Build and maintain full-stack applications using TypeScript, React and Node.js - Develop APIs (REST, tRPC, GraphQL) and manage database schemas (PostgreSQL) - Contribute to AI feature development, including LLM integrations and workflow automation - Collaborate on system design, architecture and implementation decisions - Ensure code quality through testing, reviews and best practices - Work in Agile teams and deliver production-ready features Requirements - 5+ years of full-stack development experience - Strong proficiency in TypeScript, React, Node.js - Experience with modern frameworks (Next.js, Tailwind, headless UI) - Experience with relational databases and ORMs (Prisma, Drizzle) - Hands-on experience with AWS and CI/CD pipelines - Experience with Docker - Practical experience integrating AI APIs (e.g. OpenAI) into applications - Familiarity with AI-assisted development tools (Copilot, Cursor, etc.) - Understanding of AI SDLC Nice to have - Experience with microfrontends and Single-SPA - Testing frameworks (Vitest, Playwright) - Kubernetes or infrastructure-as-code tools.

• Identify common design and implementation needs across application engineering teams • Create and maintain high-quality documentation, reference architectures, and implementation guides • Develop reusable artifacts such as Terraform or similar modules, code templates, and example implementations • Partner with enterprise platform and foundation teams • Collaborate with architects to translate architectural principles • Contribute to and evolve AI-assisted developer workflows • Evaluate and choose the right medium for enablement • Gather feedback from application teams and iterate on paved paths • Advocate for a developer-centric approach to platform adoption

• Design, build, and optimize ETL/ELT data pipelines using Azure and GCP services • Develop and maintain optimized data models within multi-cloud data warehouse solutions • Monitor and optimize the performance of data warehouse queries • Collaborate with Data Scientists to design feature stores and pipelines for ML models • Implement workflows to automate the end-to-end data lifecycle for AI/ML processes • Work with Data Science teams to deploy and manage machine learning models in production environments • Write complex SQL queries and develop scripts in Python for data manipulation