AI DevOps Engineer

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Location:

NewYork, NY

Type:

Contract

Requirements About theRole Our client is seekinga highly skilled AI DevOps Engineer to design, build, and operatescalable, secure, and production-grade infrastructure supporting modern AIplatforms and LLM-powered applications.

This role sitsat the intersection of DevOps, Platform Engineering, Site ReliabilityEngineering (SRE), and AI Infrastructure, enabling high-performance AIsystems, agent-based workflows, and enterprise AI platforms within a regulatedfinancial services environment.

The idealcandidate will have strong expertise in Kubernetes, Terraform, cloudinfrastructure, automation, and AI platform operations, along withexperience supporting modern AI/LLM workloads in production environments.

KeyResponsibilities

Design, deploy, and manage scalable infrastructurefor AI and LLM-based applications in production environments.

Build and maintain Infrastructure-as-Code (IaC)using tools such as Terraform for secure, repeatable, and auditabledeployments.

Deploy, manage, and scale containerizedenvironments using Kubernetes with a focus on high availability andreliability.

Implement DevOps, Platform Engineering, and SREbest practices to improve system reliability, scalability, and operationalefficiency.

Support AI platform services for model serving,inference, experimentation, and evaluation workflows.

Deploy and maintain infrastructure supporting AIagents, orchestration frameworks, and LLM runtime dependencies.

Design and manage vector database infrastructureincluding Pinecone, Weaviate, or PostgreSQL with pgvector for RAG andsemantic search use cases.

Enable AI developer platforms and tooling forengineering teams building AI-powered applications.

Implement monitoring, alerting, logging, andincident response processes for mission-critical AI systems.

Collaborate with security, compliance, andgovernance teams to ensure adherence to regulatory and enterprise securitystandards.

Continuously improve automation, developerexperience, and operational processes for AI infrastructure environments.

RequiredQualifications

Bachelor’s degree in Computer Science, Engineering,or equivalent practical experience.

Proven experience as a DevOps Engineer, PlatformEngineer, or Site Reliability Engineer (SRE).

Strong hands‑on experience managing large-scaleproduction infrastructure.

Expertise with Terraform and Infrastructure-as-Code(IaC) methodologies.

Strong experience deploying and operatingKubernetes-based environments.

Experience supporting infrastructure for AIplatforms or LLM-based applications.

Strong understanding of automation, scalability,reliability, and cloud-native architectures.

PreferredQualifications

Experience supporting production-grade LLMapplications and AI agent workloads.

Hands-on experience with vector databases such asPinecone, Weaviate, or pgvector.

Experience building or supporting AI tooling andinternal AI developer platforms.

Knowledge of observability, monitoring, capacityplanning, and reliability engineering for AI/ML systems.

Experience working within financial services orother highly regulated industries.

Strong communication and cross-functionalcollaboration skills.

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