AI Platform & DevSecOps Engineer

Credence•McLean, VA

6d•Onsite

About The Position

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose. We’ve been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges. Credence has an immediate need for an AI Platform & DevSecOps Engineer to support federal programs hosted within AWS GovCloud. This hands-on engineering role combines DevSecOps, cloud infrastructure, platform engineering, security automation, and AI platform enablement to support secure and reliable delivery of mission-critical applications. The engineer will design, automate, secure, and operate cloud infrastructure, CI/CD pipelines, container platforms, and shared platform services while supporting the infrastructure and operational capabilities needed for AI-enabled applications and services. The ideal candidate has a strong foundation in AWS, Kubernetes, Infrastructure as Code (IaC), CI/CD, Python, security automation, and production operations, along with practical knowledge of modern AI technologies and the infrastructure patterns used to securely deploy and operate AI-enabled solutions.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Engineering, Cybersecurity, or a related technical field, or equivalent relevant professional experience.
5+ years of hands-on experience in DevSecOps, DevOps, cloud engineering, platform engineering, software engineering, or related technical roles.
Strong hands-on experience designing, deploying, or operating workloads within AWS ; AWS GovCloud experience is highly desirable.
Hands-on experience with Docker/OCI containers and Kubernetes , preferably Amazon EKS.
Experience developing and maintaining CI/CD pipelines using GitLab CI/CD, Jenkins, AWS CodePipeline, or comparable technologies.
Strong experience with Infrastructure as Code , including Terraform, CloudFormation, or comparable technologies.
Proficiency with Python and experience using Bash, PowerShell, or similar scripting languages for automation.
Experience with Git-based development workflows, automated testing, artifact management, and modern software delivery practices.
Experience integrating security capabilities into CI/CD and cloud environments, including vulnerability scanning, secrets management, IAM, secure configuration, and automated security controls.
Experience implementing monitoring, logging, alerting, and operational troubleshooting for production or production-like environments.
Working knowledge of AI/ML and generative AI technologies , including LLMs, AI APIs, model inference, and cloud infrastructure supporting AI-enabled applications.
Experience supporting, deploying, integrating, or operating AI/ML or AI-enabled applications in cloud or containerized environments.
Understanding of cloud security principles, identity and access management, networking, encryption, secrets management, and least-privilege access.
Strong troubleshooting, technical communication, documentation, and cross-functional collaboration skills.
U.S. Citizenship with eligibility for a DoD Secret clearance.

Nice To Haves

Supporting DoD, federal civilian, or other highly regulated environments .
Hands-on experience with AWS GovCloud .
Knowledge of federal cybersecurity requirements and frameworks including RMF, NIST 800-53, NIST 800-171, FedRAMP, DISA STIGs, and Zero Trust .
Experience with Amazon Bedrock, Amazon Sagemaker, or other enterprise AI/ML platforms and services .
Familiarity with operational considerations for AI workloads, including security, observability, scalability, availability, performance, and cost.
Experience implementing CI/CD or platform automation supporting AI-enabled applications and services.
Familiarity with AI security and governance considerations within federal or regulated environments.
Experience with Helm, Argo CD, Flux, or other Kubernetes/GitOps technologies .
Experience with observability technologies such as CloudWatch, Prometheus, Grafana, OpenTelemetry, Splunk, or ELK .
Experience with software supply-chain security practices such as SBOM generation, artifact signing, provenance, container hardening, and policy enforcement.
Experience with secrets-management and security technologies such as AWS Secrets Manager, AWS KMS, HashiCorp Vault, or comparable solutions.
AWS, Kubernetes, security, DevSecOps, or AI/ML-related professional certifications.

Responsibilities

Design, build, and maintain secure, scalable platform capabilities supporting application development and delivery within AWS GovCloud.
Develop reusable infrastructure, automation, deployment patterns, and platform services that improve engineering consistency, security, and developer productivity.
Design, implement, and maintain secure, scalable, and compliant AWS GovCloud environments supporting DoD and federal applications. Work with AWS services including Amazon EKS, ECS/Fargate, IAM, VPC, S3, CloudWatch, and other approved cloud-native services.
Build, maintain, and improve CI/CD pipelines using technologies such as GitLab CI/CD, Jenkins, AWS CodePipeline, and related tooling. Automate application and infrastructure deployments while integrating testing, security scanning, compliance checks, and deployment controls into delivery workflows.
Automate infrastructure provisioning and configuration using technologies such as Terraform, CloudFormation, and Ansible. Develop reusable infrastructure components and apply version control, peer review, automated validation, and repeatable deployment practices.
Deploy and operate containerized applications using Docker/OCI containers and Kubernetes, including Amazon EKS. Support workload configuration, networking, storage, secrets, scaling, resource management, upgrades, security, and troubleshooting.
Integrate security throughout the software development lifecycle and support compliance with applicable federal cybersecurity frameworks, including NIST 800-53, NIST 800-171, RMF, FedRAMP, STIGs, and Zero Trust principles. Implement and support automated security capabilities including SAST/DAST, software composition analysis, container scanning, IaC scanning, secrets detection, vulnerability management, and compliance validation.
Support the cloud infrastructure and shared platform capabilities required to securely deploy and operate AI-enabled applications and services. Work with AI and software engineering teams to establish repeatable patterns for deployment, configuration, access control, security, monitoring, scalability, and operational support.
Support the secure integration and operation of approved AI and LLM services, including platforms such as Amazon Bedrock and other enterprise AI services. Assist engineering teams with infrastructure, authentication and authorization, API connectivity, configuration, deployment automation, monitoring, and operational troubleshooting.
Implement monitoring, logging, tracing, dashboards, and alerting across cloud infrastructure, Kubernetes, applications, and platform services using technologies such as AWS CloudWatch, Security Hub, GuardDuty, Splunk/ELK, Prometheus, Grafana, OpenTelemetry, or comparable solutions. Participate in incident response, root-cause analysis, vulnerability remediation, and continuous reliability improvements.
Develop automation and platform tooling using Python, Bash, PowerShell, or similar technologies to eliminate repetitive operational tasks, integrate services and APIs, enforce platform standards, and improve deployment efficiency.
Troubleshoot complex infrastructure, application, CI/CD, Kubernetes, networking, and cloud service issues in production and production-like environments. Support operational readiness, system reliability, capacity, performance, and continuous improvement.
Work closely with software engineers, AI engineers, cybersecurity teams, cloud engineers, architects, and mission stakeholders to integrate security, automation, and platform capabilities throughout the software development lifecycle. Develop technical documentation, architecture diagrams, runbooks, and reusable engineering standards.