AI Platform & DevSecOps Engineer

Simple Technology Solutions is looking for an AI Platform & DevSecOps Engineer to add to our team.

Quick Position Overview:

• US Citizenship and the ability to obtain and maintain a Public Trust clearance are required
• Bachelor's Degree is required
• Minimum of 8 years' position related experience is required
• AWS Solutions Architect (Associate) or DevOps Engineer (Professional) certification preferred for hire; the AWS and Anthropic Claude certifications listed under Required Certifications must be earned within 12 months of hire
• Remote position with occasional travel to client sites and STS events
• Candidates living in the DC Metro region (within driving distance for quarterly in-person team events) are strongly preferred; STS is a HUBZone company, so residence in a HUBZone is favored for remote candidates

The Role:

The AI Platform & DevSecOps Engineer owns the environments, pipelines, and controls that let an STS AI team move fast safely in federal settings. You build and operate the standard DEV, TST, STG, and PRD environments with Terraform, automate the CI/CD gates that enforce the STS SDLC, and act as the team's release manager. Success looks like releases that are routine and boring, security and compliance evidence that is generated by the pipeline rather than assembled by hand, and AI services that are guarded, observable, and cost-controlled. Because many federal contracts ask for this skill set by name, you also support client engagements that run entirely on AWS-native services.

The AI Platform & DevSecOps Engineer at STS will:

• Design, build, and maintain the STS standard environment set (DEV and TST in a nonproduction account, STG and PRD in a production account) on AWS using Terraform and reusable infrastructure modules.
• Build and operate CI/CD pipelines in GitHub Actions or the client's equivalent that enforce the STS SDLC gates, including automated test execution, coverage thresholds, security scanning, and promotion approvals between environments.
• Serve as the team's release manager, orchestrating the release-management agents and skills, coordinating releases across environments, and maintaining release notes and rollback procedures.
• Secure AI workloads on AWS, including Amazon Bedrock guardrails, model access controls, IAM least-privilege design, data encryption, logging, and network isolation for sensitive data.
• Generate and maintain security and compliance evidence for federal frameworks such as FedRAMP, NIST 800-53, and CJIS, and support the client's ATO and continuous-monitoring processes.
• Implement observability for AI applications, including application and model-call tracing, evaluation metrics, cost monitoring, and alerting across all environments.
• Stand up and administer the team's AI development tooling, including Claude Code accounts and configuration, shared agent and skill repositories, and the connections between Jira, GitHub, and the pipelines.
• Provide AWS platform engineering on client engagements that run on AWS-native services, including landing zones, account structure, and well-architected reviews.
• Automate everything that sits between requirements and end-to-end testing, so that human effort concentrates on those two bookends of the lifecycle.
• Document the platform, runbooks, and standards as reusable parts of the STS SDLC, and coach engineers on using them.

Education and Experience:

Required

• Bachelor's degree in Computer Science, Information Systems, Cybersecurity, or a related technical field, or equivalent professional experience in addition to the minimum below
• Minimum of 8 years of professional experience in DevOps, platform, cloud, or site-reliability engineering, including at least 4 years on AWS and at least 2 years supporting generative AI or machine-learning workloads
• Demonstrated experience delivering infrastructure as code with Terraform and CI/CD pipelines for a multi-environment application
• 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 equivalent), automated testing integration, container builds, and artifact and secrets management
• Working knowledge of Python or TypeScript sufficient to write automation, pipeline steps, and platform tooling
• Familiarity with Claude Code, agentic development tooling, and administering AI accounts and shared configuration for a team
• Security-minded by default while still optimizing for developer speed; treats friction in the pipeline as a bug
• Calm and methodical under release pressure, with strong attention to detail in evidence and change control
• Self-directed and comfortable owning outcomes on a small, senior team where everyone contributes across the lifecycle
• Curious and current on AI tooling; treats AI assistants as part of the team and holds their output to the same standard as human work
• Clear, candid communicator with federal clients and teammates; writes well and documents as a habit
• Bias toward fast delivery and early user feedback over conservative gating; learns from failure quickly

Required Certifications (to be earned within 12 months of hire)

• AWS Certified Solutions Architect – Associate or AWS Certified DevOps Engineer – Professional
• Claude Certified Developer – Foundations (CCDV-F) or Claude Certified Associate – Foundations (CCAO-F)

Preferred Certifications

• AWS Certified Security – Specialty
• HashiCorp Certified: Terraform Associate
• CompTIA Security+ or CISSP
• Certified Kubernetes Administrator (CKA)

What We Offer:

• Competitive compensation package
• Comprehensive health, dental, and vision insurance plans
• Professional development and training
• Performance-based incentives
• 401(k) retirement savings plan
• Work from home stipend
• Unlimited PTO
• Paid holidays
• Flexible work schedule
• Professional development budget to be used for training and certifications