DevOps Engineer - Senior Vice President
iCapital - New York, New York, United States
Posted Feb 18, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
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- Mental health support
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- Relocation assistance
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- Childcare support
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- 401(k) match
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Schedule
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Where they hire
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About this role
DevOps Engineer - Senior Vice President New York, New York, United States About the Role The Platform Infrastructure team at iCapital plays a critical role in ensuring that both production and development environments operate smoothly, securely, and reliably. This role leverages advanced cloud capabilities to support the Platform Infrastructure strategy of market agility and lean operating principles, with a strong emphasis on quality to meet the ever‑growing demands of our clients. We are seeking highly collaborative, creative, and intellectually curious MLOps/DevOps Engineers with deep expertise in machine learning operations, cloud infrastructure, CI/CD automation, Kubernetes, and security. This role requires hands‑on experience designing, building, and operating scalable DevOps and enterprise‑grade MLOps platforms, including model lifecycle automation, observability, and governance. As a Platform Engineer, you will wear multiple hats in a highly visible role, partnering closely with engineering, security, data, and business teams to deliver secure, reliable, and highly automated platforms that support both application and machine‑learning workloads. 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
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