AI DevOps Engineer

New York, United States | Posted on 05/01/2026 Do you love a career where you Experience , Grow & Contribute at the same time, while earning at least 10% above the market? If so, we are excited to have bumped onto you. Learn how we are redefining the meaning of work, and be a part of the team raved by Clients, Job-seekers and Employees. If you are a Field Service Engineer looking for excitement, challenge and stability in your work, then you would be glad to come across this page. We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details. Check if you are up for maximizing your earning/growth potential, leveraging our Disruptive Talent Solution. Location: New York, NY Type: Contract Requirements About the Role Our client is seeking a highly skilled AI DevOps Engineer to design, build, and operate scalable, secure, and production-grade infrastructure supporting modern AI platforms and LLM-powered applications. This role sits at the intersection of DevOps, Platform Engineering, Site Reliability Engineering (SRE), and AI Infrastructure , enabling high-performance AI systems, agent-based workflows, and enterprise AI platforms within a regulated financial services environment. The ideal candidate will have strong expertise in Kubernetes, Terraform, cloud infrastructure, automation, and AI platform operations , along with experience supporting modern AI/LLM workloads in production environments. Key Responsibilities Design, deploy, and manage scalable infrastructure for AI and LLM-based applications in production environments. Build and maintain Infrastructure-as-Code (IaC) using tools such as Terraform for secure, repeatable, and auditable deployments. Deploy, manage, and scale containerized environments using Kubernetes with a focus on high availability and reliability. Implement DevOps, Platform Engineering, and SRE best practices to improve system reliability, scalability, and operational efficiency. Support AI platform services for model serving, inference, experimentation, and evaluation workflows. Deploy and maintain infrastructure supporting AI agents, orchestration frameworks, and LLM runtime dependencies. Design and manage vector database infrastructure including Pinecone, Weaviate, or PostgreSQL with pgvector for RAG and semantic search use cases. Enable AI developer platforms and tooling for engineering teams building AI-powered applications. Implement monitoring, alerting, logging, and incident response processes for mission-critical AI systems. Collaborate with security, compliance, and governance teams to ensure adherence to regulatory and enterprise security standards. Continuously improve automation, developer experience, and operational processes for AI infrastructure environments. Required Qualifications Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. Proven experience as a DevOps Engineer, Platform Engineer, or Site Reliability Engineer (SRE). Strong hands‑on experience managing large‑scale production infrastructure. Expertise with Terraform and Infrastructure-as-Code (IaC) methodologies. Strong experience deploying and operating Kubernetes-based environments. Experience supporting infrastructure for AI platforms or LLM-based applications. Strong understanding of automation, scalability, reliability, and cloud-native architectures. Preferred Qualifications Experience supporting production‑grade LLM applications and AI agent workloads. Hands‑on experience with vector databases such as Pinecone, Weaviate, or pgvector. Experience building or supporting AI tooling and internal AI developer platforms. Knowledge of observability, monitoring, capacity planning, and reliability engineering for AI/ML systems. Experience working within financial services or other highly regulated industries. Strong communication and cross‑functional collaboration skills. #J-18808-Ljbffr