Senior AI Cloud Engineer with Security Clearance

Senior / Lead Cloud AI Engineer Overview
We're seeking a Senior/Lead Cloud AI Engineer to design, build, and operate secure, mission-ready AI capabilities in federal cloud environments. This role blends cloud engineering, MLOps, and AI/ML engineering to deliver scalable, compliant solutions—from data pipelines and model training to deployment, monitoring, and continuous improvement—often in regulated or classified settings. Key Responsibilities
• Cloud & Platform Engineering (AI-Ready Foundations)
• Design, implement, and maintain cloud infrastructure and platform services (AWS, Azure, or GCP) that support AI/ML workloads in secure federal environments.
• Build and manage Infrastructure-as-Code (IaC) and automated configuration for repeatable environments using tools such as Terraform or native cloud templates.
• Develop and maintain CI/CD pipelines enabling automated build, test, and deployment of cloud and AI services.
• Implement containerized and orchestrated runtime environments for AI services using Docker and Kubernetes/OpenShift.
• Engineer reliability, scalability, and performance through automation, monitoring, and operational best practices. AI / ML Engineering & MLOps
• Develop and deploy AI/ML solutions, including traditional machine learning and generative AI use cases.
• Design and operate production-grade MLOps pipelines for model training, testing, deployment, versioning, and rollback.
• Implement monitoring for model performance, drift, bias, and operational health.
• Integrate AI capabilities with enterprise systems, APIs, and cloud-native data pipelines.
• Support responsible AI practices, governance, and lifecycle management. Security, Compliance, and Federal Delivery
• Partner with cybersecurity and compliance teams to implement security controls and support federal accreditation processes.
• Produce technical documentation and evidence artifacts supporting authorization to operate (ATO) and continuous monitoring.
• Implement secure identity and access management, logging, and auditability aligned with federal standards.
• Lead technical solutioning efforts and mentor junior engineers.
• Communicate complex technical solutions clearly to both technical and non-technical stakeholders. Required Qualifications
• 8+ years of experience in cloud engineering, DevOps, platform engineering, or systems engineering, with senior-level responsibility.
• 3+ years of hands-on experience delivering AI/ML solutions and operating MLOps pipelines in production.
• Strong experience with at least one major cloud provider (AWS, Azure, or GCP).
• Hands-on experience with CI/CD automation, Infrastructure-as-Code, and DevSecOps practices.
• Proficiency with container technologies (Docker) and orchestration platforms (Kubernetes or OpenShift).
• Strong scripting or programming experience (Python strongly preferred).
• Experience implementing logging, monitoring, alerting, and audit controls in regulated environments. Preferred Qualifications
• Experience supporting federal or highly regulated cloud environments (e.g., GovCloud, classified or restricted partitions).
• Familiarity with federal cybersecurity frameworks and compliance activities.
• Experience modernizing legacy systems into cloud-native, AI-enabled architectures.
• Background building AI platforms, including model hosting, vector search, retrieval-augmented generation (RAG), and orchestration frameworks. Clearance / Work Environment
Ability to obtain and maintain a federal security clearance; active clearance may be required depending on the program.
Onsite or hybrid work may be required based on mission and program needs. Certifications (Preferred)
• Cloud certifications (AWS, Azure, or GCP).
• Security baseline certifications may be required on some programs. Example Technologies
• Cloud: AWS, Azure, GCP
• IaC: Terraform, CloudFormation, ARM
• CI/CD: GitLab CI, GitHub Actions, Azure DevOps
• Containers: Docker, Kubernetes, OpenShift
• AI/ML: PyTorch, TensorFlow, managed cloud AI services
• Observability/Security: Centralized logging, monitoring, audit trails, policy enforcement Education
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Compensation and Benefits
Salary Range: $180,000 - $250,000/yr (Compensation is determined by various factors, including but not limited to location, work experience, skills, education, certifications, seniority, and business needs. This range may be modified in the future.) Benefits: Gridiron offers a comprehensive benefits package including medical, dental, vision insurance, HSA, FSA, 401(k), disability & ADD insurance, life and pet insurance to eligible employees. Full-time and part-time employees working at least 30 hours per week on a regular basis are eligible to participate in Gridiron's benefits programs. Gridiron IT Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status or disability status. Gridiron IT is a Women Owned Small Business (WOSB) headquartered in the Washington, D.C. area that supports our clients' missions throughout the United States. Gridiron IT specializes in providing comprehensive IT services tailored to meet the needs of federal agencies. Our capabilities include IT Infrastructure & Cloud Services, Cyber Security, Software Integration & Development, Data Solution & AI, and Enterprise Applications. These capabilities are backed by Gridiron IT's experienced workforce and our commitment to ensuring we meet and exceed our clients' expectations.

Senior / Lead Cloud AI Engineer Overview
We're seeking a Senior/Lead Cloud AI Engineer to design, build, and operate secure, mission-ready AI capabilities in federal cloud environments. This role blends cloud engineering, MLOps, and AI/ML engineering to deliver scalable, compliant solutions—from data pipelines and model training to deployment, monitoring, and continuous improvement—often in regulated or classified settings. Key Responsibilities
• Cloud & Platform Engineering (AI-Ready Foundations)
• Design, implement, and maintain cloud infrastructure and platform services (AWS, Azure, or GCP) that support AI/ML workloads in secure federal environments.
• Build and manage Infrastructure-as-Code (IaC) and automated configuration for repeatable environments using tools such as Terraform or native cloud templates.
• Develop and maintain CI/CD pipelines enabling automated build, test, and deployment of cloud and AI services.
• Implement containerized and orchestrated runtime environments for AI services using Docker and Kubernetes/OpenShift.
• Engineer reliability, scalability, and performance through automation, monitoring, and operational best practices. AI / ML Engineering & MLOps
• Develop and deploy AI/ML solutions, including traditional machine learning and generative AI use cases.
• Design and operate production-grade MLOps pipelines for model training, testing, deployment, versioning, and rollback.
• Implement monitoring for model performance, drift, bias, and operational health.
• Integrate AI capabilities with enterprise systems, APIs, and cloud-native data pipelines.
• Support responsible AI practices, governance, and lifecycle management. Security, Compliance, and Federal Delivery
• Partner with cybersecurity and compliance teams to implement security controls and support federal accreditation processes.
• Produce technical documentation and evidence artifacts supporting authorization to operate (ATO) and continuous monitoring.
• Implement secure identity and access management, logging, and auditability aligned with federal standards.
• Lead technical solutioning efforts and mentor junior engineers.
• Communicate complex technical solutions clearly to both technical and non-technical stakeholders. Required Qualifications
• 8+ years of experience in cloud engineering, DevOps, platform engineering, or systems engineering, with senior-level responsibility.
• 3+ years of hands-on experience delivering AI/ML solutions and operating MLOps pipelines in production.
• Strong experience with at least one major cloud provider (AWS, Azure, or GCP).
• Hands-on experience with CI/CD automation, Infrastructure-as-Code, and DevSecOps practices.
• Proficiency with container technologies (Docker) and orchestration platforms (Kubernetes or OpenShift).
• Strong scripting or programming experience (Python strongly preferred).
• Experience implementing logging, monitoring, alerting, and audit controls in regulated environments. Preferred Qualifications
• Experience supporting federal or highly regulated cloud environments (e.g., GovCloud, classified or restricted partitions).
• Familiarity with federal cybersecurity frameworks and compliance activities.
• Experience modernizing legacy systems into cloud-native, AI-enabled architectures.
• Background building AI platforms, including model hosting, vector search, retrieval-augmented generation (RAG), and orchestration frameworks. Clearance / Work Environment
Ability to obtain and maintain a federal security clearance; active clearance may be required depending on the program.
Onsite or hybrid work may be required based on mission and program needs. Certifications (Preferred)
• Cloud certifications (AWS, Azure, or GCP).
• Security baseline certifications may be required on some programs. Example Technologies
• Cloud: AWS, Azure, GCP
• IaC: Terraform, CloudFormation, ARM
• CI/CD: GitLab CI, GitHub Actions, Azure DevOps
• Containers: Docker, Kubernetes, OpenShift
• AI/ML: PyTorch, TensorFlow, managed cloud AI services
• Observability/Security: Centralized logging, monitoring, audit trails, policy enforcement Education
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Compensation and Benefits
Salary Range: $180,000 - $250,000/yr (Compensation is determined by various factors, including but not limited to location, work experience, skills, education, certifications, seniority, and business needs. This range may be modified in the future.) Benefits: Gridiron offers a comprehensive benefits package including medical, dental, vision insurance, HSA, FSA, 401(k), disability & ADD insurance, life and pet insurance to eligible employees. Full-time and part-time employees working at least 30 hours per week on a regular basis are eligible to participate in Gridiron's benefits programs. Gridiron IT Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status or disability status. Gridiron IT is a Women Owned Small Business (WOSB) headquartered in the Washington, D.C. area that supports our clients' missions throughout the United States. Gridiron IT specializes in providing comprehensive IT services tailored to meet the needs of federal agencies. Our capabilities include IT Infrastructure & Cloud Services, Cyber Security, Software Integration & Development, Data Solution & AI, and Enterprise Applications. These capabilities are backed by Gridiron IT's experienced workforce and our commitment to ensuring we meet and exceed our clients' expectations.

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