AI Platform & DevSecOps Engineer

Job summary

The AI Platform & DevSecOps Engineer builds and operates secure, multi-environment AWS platforms and delivery pipelines for AI workloads in federal and regulated settings. Responsibilities include managing infrastructure with Terraform, enforcing CI/CD controls, coordinating releases, securing Amazon Bedrock services, and automating compliance evidence and observability. The role also supports AWS-native client platforms and administers AI development tooling such as Claude Code.

Benefits

Qualifications

• At least 8 years of professional experience in DevOps, platform, cloud, or site-reliability engineering, including at least 4 years on AWS and 2 years supporting generative AI or machine-learning workloads.
• Demonstrated experience delivering Terraform infrastructure as code and CI/CD pipelines for multi-environment applications.
• Experience supporting a federal or regulated system through an authorization process such as FedRAMP, RMF/ATO, or CJIS compliance.
• Expert-level Terraform and AWS skills, including multi-account organization, IAM, VPC networking, KMS, CloudWatch, CloudTrail, and Security Hub.
• Hands-on experience securing and operating Amazon Bedrock and related AI services, including guardrails, model access, and usage and cost controls.
• Strong CI/CD skills with GitHub Actions or an equivalent, including automated testing, container builds, and artifact and secrets management.
• Working knowledge of Python or TypeScript for automation, pipeline steps, and platform tooling.
• Familiarity with Claude Code, agentic development tooling, and administration of AI accounts and shared team configuration.
• U.S. citizenship and ability to obtain and maintain a Public Trust clearance.
• Required AWS and Claude certifications must be earned within 12 months of hire.
• DC Metro-area residence is preferred.

Responsibilities

• Design, build, and maintain DEV, TST, STG, and PRD AWS environments using Terraform and reusable infrastructure modules.
• Build and operate CI/CD pipelines that enforce SDLC gates, including automated tests, coverage thresholds, security scans, and promotion approvals.
• Coordinate releases across environments and maintain release notes and rollback procedures.
• Secure AWS AI workloads using Amazon Bedrock guardrails, model access controls, least-privilege IAM, encryption, logging, and network isolation.
• Generate and maintain evidence for FedRAMP, NIST 800-53, and CJIS compliance and support authorization and continuous-monitoring processes.
• Implement AI application observability, including tracing, evaluation metrics, cost monitoring, and alerting.
• Administer Claude Code accounts and configuration, shared agent and skill repositories, and Jira, GitHub, and pipeline integrations.
• Provide AWS platform engineering for client engagements, including landing zones, account structures, and well-architected reviews.
• Automate lifecycle tasks between requirements and end-to-end testing.
• Document platforms, runbooks, and standards, and coach engineers on their use.

Skills

Certifications

Degrees

Work schedule

Travel

Industry

Security clearance

Relocation