DevOps AI Cloud Engineer / Onsite in Raleigh, NC

Tech Breakdown

• 60% DevOps / Cloud Infrastructure (AWS, Terraform, Kubernetes, CI/CD)
• 40% AI/ML Integration & Platform Development (Bedrock, LLMs, GenAI tools)

Daily Responsibilities

• 40% Designing and building scalable AI platform infrastructure
• 30% Implementing and optimizing CI/CD pipelines and cloud environments
• 20% Integrating and deploying AI/GenAI solutions and LLM-based applications
• 10% Staying current with AI regulations, governance, and best practices

The Offer

• 15% annual bonus
• Hybrid work model (Raleigh - onsite 3 days/week)
• Opportunity to join a growing AI-focused team at an early stage
• Work on high-impact, cutting-edge AI and cloud initiatives

This Raleigh-based organization is seeking a Hybrid AI Cloud Engineer (DevOps-focused) to join a small but rapidly growing team, working onsite 3 days per week. This role blends modern DevOps practices with cutting-edge Generative AI, leveraging technologies such as AWS, Terraform, Kubernetes (EKS), Jenkins CI/CD, and Amazon Bedrock. The position is ideal for a mid-level engineer who is eager to deepen their experience in AI infrastructure while contributing to a highly impactful platform buildout.

This is a unique opportunity to work directly alongside early AI/ML hires, helping shape the organization’s cloud and AI strategy from the ground up. The engineer in this role will drive real innovation-building scalable systems that operationalize AI, integrating LLMs into production environments, and enabling automation across the business. Strong learning agility, curiosity around AI tooling, and a hands-on mindset will set candidates apart. Required Skills & Experience

• 3-6+ years of experience in DevOps, Cloud Engineering, or similar
• Strong experience with AWS cloud services
• Infrastructure as Code expertise with Terraform
• Experience with containerization (Docker) and orchestration via Kubernetes / EKS
• CI/CD pipeline experience, preferably with Jenkins
• Hands-on exposure to Generative AI tools (e.g., Amazon Bedrock, OpenAI APIs, or similar)
• Experience working with or integrating Large Language Models (LLMs)
• Ability to deploy, manage, and scale cloud-native systems
• Strong understanding of system reliability, monitoring, and automation
• Solid communication skills and ability to work in a collaborative team environment

Desired Skills & Experience

• Experience building or contributing to MLOps platforms or AI infrastructure
• Exposure to AI governance, compliance, or regulatory frameworks
• Familiarity with Python or similar scripting languages for automation
• Experience building or deploying AI agents or GenAI-based applications
• Knowledge of security best practices in cloud and AI environments
• Startup or early-stage team experience (comfort with ambiguity and rapid change)