Senior AI DevOps Engineer (AI Ops / Platform Engineering)

DeepCamp; Tucker (GA); On-site; USD 96,000 - 165,000; Full time

Job summary

DeepCamp seeks a Senior AI DevOps Engineer to lead the design and delivery of AI-powered software delivery and cloud operations. You will merge modern DevOps with Generative AI, MCP, and intelligent automation to transform how teams build, deploy, and operate software.

You will collaborate with Platform Engineering, DevOps, Security, SRE, and AI groups to craft secure, scalable cloud-native solutions that boost reliability, observability, and efficiency.

Qualifications

• 7+ years in DevOps/SRE/Cloud/Platform Engineering.
• 4+ years designing and supporting enterprise CI/CD pipelines.
• 3+ years cloud engineering in AWS/Azure/GCP (AWS preferred).
• Strong experience with Kubernetes and Docker in production.
• Hands-on IaC with Terraform/OpenTofu/Pulumi/Terragrunt/CloudFormation.
• Strong programming skills (Python/TypeScript/JavaScript/Bash/Go).
• Experience integrating enterprise LLM platforms (OpenAI/Anthropic).
• Experience with AI orchestration frameworks (LangChain).
• Experience with MCP clients/servers.
• Experience DevSecOps: SAST/DAST/Secrets management.

Responsibilities

• Design and optimize AI-enabled CI/CD pipelines to boost productivity and quality.
• Develop MCP clients/servers to connect enterprise LLMs with tools and infra.
• Build MCP services using Python/TypeScript/Node.js to expose data to AI agents.
• Integrate LLM-powered workflows for code review, testing, security analysis, and deployment guidance.
• Maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, CircleCI, ArgoCD.
• Implement AI-driven ChatOps for interacting with deployment pipelines and cloud tools.
• Design remediation workflows for incident detection and troubleshooting.
• Develop IaC automation using Terraform/OpenTofu/Pulumi/Terragrunt/CloudFormation.

Skills

DevOps

SRE

CI/CD

Cloud AWS

Kubernetes

Docker

IaC (Terraform/OpenTofu/Pulumi)

Python/TypeScript/JavaScript

LangChain/LLM tools

MCP (Model Context Protocol)

DevSecOps

Secrets management

Observability (Datadog/Grafana/Prom)**

Education

Bachelor's degree in Computer Science or related field

Tools

Kubernetes

Docker

GitHub Actions

GitLab CI

Jenkins

CircleCI

ArgoCD

Terraform/OpenTofu/Pulumi

CloudFormation

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 AIMS 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).