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Aws Devsecops Engineer Jobs in Georgia (NOW HIRING)

Lorven Technologies

Devops Engineer

Alpharetta, GA · On-site

$51.50 - $70.50/hr

Manage and automate resources across on-prem (VMware) and Cloud (AWS/Azure/GCP). You will be ... DevSecOps): Integrate automated security scanning (Snyk, SonarQube, Prisma) into the pipeline. In ...

Saransh Inc

Data Scientist - Need locals

Duluth, GA · On-site

Set up observability dashboards and optimize AWS costs * Collaborate with data engineers/scientists to enable scalable, secure data platforms * Enforce DevSecOps best practices and support production ...

Staffingine LLC

Java full stack developer

Atlanta, GA · On-site

$50.50 - $65.25/hr

Minimum of 7 years in IT, including 4 years of hands-on software development in DevSecOps and ... Demonstrated experience with AWS cloud services * Application development expertise in Java ...

Shoptalk

Senior Data & ML Engineer

Alpharetta, GA · On-site

$140 - $210/hr

Build scalable ETL and data integration workflows using Python, SQL, AWS Glue, Qlik Data ... Experience with CI/CD, DevSecOps, version control, automated testing, and release management ...

Fiserv, Inc.

Senior Data & ML Engineer

Alpharetta, GA · On-site

$103K - $140K/yr

Build scalable ETL and data integration workflows using Python, SQL, AWS Glue, Qlik Data ... Experience with CI/CD, DevSecOps, version control, automated testing, and release management ...

Monitise

Senior Data & ML Engineer

Alpharetta, GA · On-site

$103K - $140K/yr

Build scalable ETL and data integration workflows using Python, SQL, AWS Glue, Qlik Data ... Experience with CI/CD, DevSecOps, version control, automated testing, and release management ...

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Aws Devsecops Engineer information

What is an AWS DevSecOps Engineer?

An AWS DevSecOps Engineer is a professional who integrates security practices into the DevOps process on Amazon Web Services (AWS). They are responsible for automating security measures, monitoring system vulnerabilities, and ensuring compliance throughout the software development lifecycle. Their role bridges the gap between development, operations, and security teams, enabling faster and more secure deployment of applications. Typical tasks include configuring security tools, managing cloud infrastructure, and implementing best practices for secure code delivery.

How does an AWS DevSecOps Engineer typically collaborate with development and security teams in a cloud environment?

As an AWS DevSecOps Engineer, you'll work closely with both development and security teams to integrate security practices into the software development lifecycle. This often involves setting up automated security checks in CI/CD pipelines, advising developers on secure coding practices, and ensuring compliance with security policies. Regular meetings and collaborative troubleshooting are common, as you'll be bridging gaps between rapid development and stringent security requirements. By fostering communication and shared responsibility, you help create a culture where security is integrated rather than added as an afterthought.

What are the key skills and qualifications needed to thrive as an AWS DevSecOps Engineer?

To thrive as an AWS DevSecOps Engineer, you need a strong background in cloud infrastructure (especially AWS), security best practices, and automation, often supported by a degree in computer science or a related field. Familiarity with tools like AWS CloudFormation, Terraform, Jenkins, Docker, Kubernetes, and security frameworks such as CIS benchmarks or AWS Security Hub is typical, along with certifications like AWS Certified DevOps Engineer or AWS Certified Security Specialty. Strong problem-solving skills, effective communication, and a proactive approach to security make someone excel in this role. These skills are crucial for ensuring secure, efficient, and resilient cloud environments that support rapid development and deployment cycles.

What is the difference between Aws Devsecops Engineer vs Cloud Security Engineer?

AspectAws Devsecops EngineerCloud Security Engineer
CertificationsAWS Certified DevOps Engineer, Security+CISSP, CCSP, AWS Security Specialty
Work EnvironmentDevOps teams, cloud infrastructure, automationSecurity teams, cloud environments, risk assessment
Primary FocusIntegrating security into DevOps pipelines on AWSImplementing and managing security measures in cloud platforms

The Aws Devsecops Engineer focuses on embedding security practices within DevOps workflows on AWS, emphasizing automation and continuous integration. In contrast, the Cloud Security Engineer concentrates on securing cloud infrastructure, managing security policies, and risk mitigation across cloud environments. Both roles require cloud security knowledge but differ in their primary responsibilities and work settings.

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Aws Devsecops Engineer jobs near you
Infographic showing various Aws Devsecops Engineer job openings in Georgia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior AI DevOps Engineer (AI Ops / Platform Engineering)

VDart, Inc.

Atlanta, GA • On-site

$125K - $160K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Role: Senior AI DevOps Engineer (AI Ops / Platform Engineering)

Location: Atlanta (Onsite)

Type: Contract

Position Summary

  • We're looking for an experienced Senior AI DevOps Engineer to help build the next generation of AI-powered software delivery and cloud operations. In this role, you'll combine modern DevOps practices with Generative AI, LLM agents, Model Context Protocol (MCP), and intelligent automation to transform how engineering teams build, deploy, and operate software.
  • You'll partner with Platform Engineering, DevOps, Security, SRE, and AI teams to design secure, scalable, cloud-native solutions that accelerate software delivery while improving reliability, observability, and operational efficiency.
  • This is an opportunity to work on cutting-edge AI technologies that are redefining modern software engineering.

What You'll Do:

  • Design, build, and optimize AI-enabled CI/CD pipelines that improve developer productivity, deployment speed, and software quality.
  • Develop and deploy Model Context Protocol (MCP) clients and servers that securely connect enterprise LLMs with engineering tools, cloud infrastructure, and operational platforms.
  • Build custom MCP services using Python, TypeScript, JavaScript, or Node.js to expose infrastructure, deployment, monitoring, and operational data to authorized AI agents.
  • Integrate LLM-powered workflows for automated code reviews, testing, security analysis, release validation, and infrastructure recommendations.
  • Build and maintain enterprise CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, CircleCI, ArgoCD, or similar platforms.
  • Implement AI-driven ChatOps capabilities that enable engineers to interact with deployment pipelines, cloud environments, and operational tools through secure conversational interfaces.
  • Design intelligent remediation workflows for incident detection, root cause analysis, log analysis, and operational troubleshooting.
  • Develop secure Infrastructure-as-Code automation using Terraform, OpenTofu, Pulumi, Terragrunt, CloudFormation, or similar technologies.
  • Deploy and manage containerized applications using Kubernetes and Docker across AWS, Azure, or Google Cloud.
  • Build AI-powered observability solutions leveraging Datadog, Prometheus, Grafana, CloudWatch, Splunk, Dynatrace, ELK, or similar platforms.
  • Implement security guardrails including RBAC, least-privilege access, approval workflows, audit logging, rollback mechanisms, and secure AI tool access.
  • Partner with Engineering, Platform, Security, SRE, and AI teams to identify and implement intelligent automation opportunities.
  • Create reusable automation frameworks, documentation, dashboards, and engineering best practices that scale across the organization.

Required Qualifications

  • 7+ years of experience in DevOps, Platform Engineering, Site Reliability Engineering (SRE), Cloud Engineering, or Infrastructure Automation.
  • 4+ years designing and supporting enterprise CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, CircleCI, ArgoCD, or similar tools.
  • 3+ years of cloud engineering experience in AWS, Azure, or Google Cloud (AWS preferred).
  • Strong experience deploying and managing Kubernetes and Docker in production environments (EKS, AKS, or GKE).
  • Hands-on experience with Infrastructure as Code using Terraform, OpenTofu, Pulumi, Terragrunt, CloudFormation, or similar tools.
  • Strong programming skills in Python, TypeScript, JavaScript, Bash, Go, or similar languages.
  • Experience integrating enterprise LLM platforms such as OpenAI, Anthropic, or equivalent AI services into engineering workflows.
  • Experience with AI orchestration frameworks such as LangChain, CrewAI, LlamaIndex, or similar technologies.
  • Experience designing or implementing Model Context Protocol (MCP) clients and servers.
  • Experience implementing DevSecOps practices including SAST, DAST, dependency scanning, container security, secrets management, and vulnerability management.
  • Experience with secrets management solutions such as HashiCorp Vault, AWS Secrets Manager, or Azure Key Vault.
  • Strong experience with monitoring, logging, and observability platforms such as Datadog, Grafana, Prometheus, CloudWatch, Splunk, Dynatrace, or ELK.
  • Excellent troubleshooting skills across cloud infrastructure, CI/CD pipelines, Kubernetes, and production systems.
  • Strong communication skills and the ability to collaborate across engineering, security, and AI teams.

Preferred Qualifications

  • Experience building AI-assisted infrastructure provisioning and deployment workflows.
  • Experience implementing autonomous or AI-assisted incident response and operational remediation.
  • Experience with MLOps platforms including MLflow, Amazon SageMaker, Vertex AI, Azure ML, or similar technologies.
  • Experience implementing human-in-the-loop approval workflows for AI-generated operational actions.
  • Knowledge of Policy-as-Code frameworks such as Open Policy Agent (OPA), Sentinel, or Checkov.
  • Experience with GitOps platforms such as ArgoCD or Flux.
  • Experience working within regulated industries such as financial services, healthcare, insurance, or government.
  • AWS, Kubernetes, DevOps, Security, or AI/ML certifications.

What Makes You Successful

  • Passion for automation and continuously improving engineering productivity.
  • Security-first mindset with practical experience implementing safe, responsible AI automation.
  • Ability to bridge DevOps, Platform Engineering, AI, Security, and Software Engineering disciplines.
  • Strong problem-solving skills with an ownership mentality from design through production support.
  • Comfortable leading technical initiatives and mentoring engineering teams on modern AI-enabled development practices.

Education

  • Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline (or equivalent professional experience).

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