M

Senior Data Infrastructure Engineer

meeboss United State
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AI Summary

Design and secure scalable cloud infrastructure for an enterprise-grade AI data platform handling sensitive financial data. Build data ingestion pipelines, Kubernetes environments, and observability systems to support LLM inference and ML workloads. Requires 6-10+ years of experience in cloud infrastructure, Kubernetes, and data pipelines with a focus on security and governance.

Key Highlights
Build infrastructure for large volumes of sensitive financial data with tenant isolation
Support LLM inference, AI agents, and ML workloads in a high-impact environment
Visa transfers supported (OPT / H-1B transfers)
Key Responsibilities
Design scalable cloud infrastructure for AI-powered data platforms
Build secure private-cloud and BYOC environments
Develop data ingestion pipelines for structured and unstructured data
Support LLM inference, AI agents, and ML workloads
Build monitoring, alerting, and observability systems
Implement access controls, audit trails, and data governance
Build CI/CD and Infrastructure-as-Code across multiple clouds
Partner with AI Research and Product teams on platform architecture
Technical Skills Required
Kubernetes Cloud Infrastructure Data Pipelines
Benefits & Perks
Visa Transfers Supported (OPT / H-1B transfers)
Equity

Job Description


About the job


MeeBoss is sharing this active opportunity on behalf of Cognistack. The hiring company is seeking an Infrastructure Engineer to build and secure the infrastructure behind an enterprise-grade AI data platform.


This role involves solving complex infrastructure challenges related to cloud, Kubernetes, data pipelines, security, and AI workloads within a high-impact, early-stage environment.


Job title


Data Infrastructure Engineer


Company


MeeBoss


Location


San Francisco, CA or New York, NY


Compensation


$150K–$300K + Equity


Why this role


  • Opportunity to build infrastructure handling large volumes of sensitive financial data.
  • Work on real-time connections between public data and private, tenant-isolated customer data.
  • Support LLM inference, AI agents, and ML workloads.
  • Visa transfers supported (OPT / H-1B transfers).


What you will do


  • Design scalable cloud infrastructure for AI-powered data platforms.
  • Build secure private-cloud and BYOC environments.
  • Develop data ingestion pipelines for structured and unstructured data.
  • Support LLM inference, AI agents, and ML workloads.
  • Build monitoring, alerting, and observability systems.
  • Implement access controls, audit trails, and data governance.
  • Build CI/CD and Infrastructure-as-Code across multiple clouds.
  • Partner with AI Research and Product teams on platform architecture.


What we are looking for


  • 6–10+ years of cloud, infrastructure, platform, or data infrastructure experience.
  • Strong experience with AWS, GCP, or Azure.
  • Production Kubernetes and containerization experience.
  • Strong infrastructure or data-pipeline experience.
  • ETL, data ingestion, or distributed processing experience.
  • Experience with Datadog or similar observability tooling.
  • Security, data governance, or regulated-industry experience.
  • Exposure to SageMaker, Bedrock, or other AI infrastructure.
  • Startup or high-growth engineering experience.
  • Strong ownership and a track record of increasing scope.


Benefits


  • Visa Transfers Supported (OPT / H-1B transfers).


About MeeBoss


MeeBoss helps job seekers and hiring teams make direct, relevant career connections.


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