Senior MLOps Platform Engineer

iCapital Network; New York (NY); Hybrid; USD 180,000 - 230,000; Full time

Benefits offered by this job

Equity

Annual bonus

Comprehensive benefits

Generous PTO

Job summary

iCapital Network's Platform Infrastructure team seeks a highly collaborative MLOps/DevOps Engineer to design, build, and operate scalable, secure platforms for ML workloads on AWS. You will partner with engineering, security, data, and business teams to deliver reliable, automated systems across production and development environments.

Responsibilities include implementing ML lifecycle pipelines, CI/CD for AI services, Terraform-driven infra, model versioning, observability, cost optimization,

Qualifications

• 15+ years of experience in DevOps, SRE, or Platform Engineering (AWS focus).
• Production ML systems deployment and monitoring experience.
• Hands-on AWS SageMaker expertise required.
• Kubernetes, containers, and cloud networking proficiency.
• CI/CD pipelines with GitLab CI or ArgoCD.
• Terraform and Python scripting proficiency.
• Strong Linux and troubleshooting fundamentals.
• Excellent cross-team communication abilities.
• Experience with MLOps platforms and tooling (model registries, experiment tracking, feature stores).
• Experience with Generative AI/LLM workloads in production.
• Familiarity with Postgres, DynamoDB, object storage.
• Fintech/regulatory environment exposure.
• Cost optimization for compute workloads.
• AWS certifications are a plus.

Responsibilities

• Design, build, and operate MLOps pipelines supporting the full ML lifecycle (training, validation, deployment, monitoring).
• Enable production workloads for AI/ML and Generative AI systems, including LLM-based services.
• Develop and maintain CI/CD pipelines for AI/ML services and supporting infrastructure.
• Build and manage cloud-native infrastructure on AWS, with heavy use of Kubernetes and containerized workloads.
• Automate infrastructure provisioning and configuration using Infrastructure as Code (Terraform).
• Implement model versioning, experiment tracking, and artifact management across environments.
• Ensure reliability, scalability, observability, and cost efficiency of AI platforms.
• Partner with AI/ML engineers to operationalize models and standardize deployment patterns.
• Implement monitoring and alerting for system health, model performance, and drift.
• Enforce security, compliance, and governance requirements for AI workloads.
• Participate in incident response, root cause analysis, and continuous improvement initiatives.
• Document standards, best practices, and reference architectures for MLOps and AI infrastructure.

Skills

AWS

Kubernetes

CI/CD pipelines

Terraform

Python scripting

Linux fundamentals

SageMaker

Security governance

Observability

Cost optimization

Model versioning

LLM workloads

GitLab CI

ArgoCD

Tools

GitLab CI

ArgoCD

Job description

iCapital Network's Platform Infrastructure team seeks a highly collaborative MLOps/DevOps Engineer to design, build, and operate scalable, secure platforms for ML workloads on AWS. You will partner with engineering, security, data, and business teams to deliver reliable, automated systems across production and development environments.

Responsibilities include implementing ML lifecycle pipelines, CI/CD for AI services, Terraform-driven infra, model versioning, observability, cost optimization,