Platform Ops

6 days ago

Frisco, United States ZipRecruiter Full time

Job DescriptionJob Description

Candidate must go to ExoSoft's client location in Frisco TX or Bellevue WA 3-5 days every week depending on client needs. Valid prior job references are must.

Employment Type

  • Corp-to-Corp
  • 1099 individuals
  • W2 full-time is negotiable.

Candidate Employment Status

  • US
  • US Green-Card / GC EAD
  • Valid H1B with minimum 1+Yr validity
  • No OPT-EAD

Job Description:

We are seeking a highly skilled and motivated Platform Ops Engineer to manage and optimize the operational performance of Open AI GPT and related AI platforms across our enterprise. The role focuses on ensuring efficient, scalable, and secure operations for AI-based products and services, including large models (LLMs) and custom GPT solutions.

The ideal candidate will have a blend of expertise in AI/ML model operations, DevOps, infrastructure management, and strong problem-solving skills to support mission-critical AI applications.

Key Responsibilities:

AI/LLM Operations & Monitoring:

  • Manage the day-to-day operations of Open AI GPT models and other AI/ML platforms.
  • Implement automated monitoring and alerting for model performance, drift, and infrastructure health.
  • Ensure high availability, reliability, and scalability of deployed GPT models across the enterprise.
  • Optimize resource allocation and scaling for large model deployments, ensuring cost-effectiveness.

Automation & CI/CD Pipelines:

  • Design and maintain automated CI/CD pipelines for rapid deployment of AI/ML models.
  • Collaborate with data science and engineering teams to streamline model retraining and updates.
  • Integrate MLOps tools and platforms (e.g., Kubeflow, MLflow, or other AI orchestration tools).

Security & Compliance:

  • Implement and manage security policies around data privacy, model access, and infrastructure security.
  • Ensure AI platforms adhere to enterprise-level compliance and governance standards.
  • Identify and mitigate risks related to AI model vulnerabilities and data usage.

Infrastructure Management:

  • Administer cloud-based infrastructure (e.g., Azure,) used for AI/ML model deployment.
  • Handle model orchestration, scaling, and optimization in containerized environments (Kubernetes, Docker).
  • Support hybrid cloud/on-prem infrastructure setups where required.

Collaboration & Stakeholder Management:

  • Work closely with data scientists, AI engineers, and product teams to align AI Ops activities with business goals.
  • Serve as the central point of contact for troubleshooting AI-related issues, providing root-cause analysis, and addressing performance bottlenecks.
  • Document operational workflows, best practices, and post-mortem analyses for continuous improvement.

Proactive Issue Resolution:

  • Use predictive analytics and anomaly detection techniques to prevent AI platform issues before they impact the business.
  • Lead incident management for AI platform disruptions and resolve operational issues in a timely manner.

Experience:

  • 5+ years of experience in AI Ops, MLOps, DevOps, or platform operations.
  • Proven expertise with AI/ML platforms, especially Open AI GPT, other LLMs, or enterprise-grade AI services.

Technical Expertise:

  • Hands-on experience with cloud platforms Preferably Azure for AI/ML deployments.
  • Proficiency with AI frameworks and libraries (TensorFlow, PyTorch, etc.).
  • Experience with CI/CD tools (Jenkins, GitLab, CircleCI) and infrastructure-as-code (Terraform, Ansible).
  • Familiarity with containerization (Docker, Kubernetes) and orchestration tools.
  • Understanding of AI model lifecycle management, versioning, and governance.

Skills:

  • Strong scripting/programming skills (Python, Bash, etc.).
  • Analytical and problem-solving mindset with the ability to address complex operational issues.
  • Excellent communication skills to engage with cross-functional teams and present solutions to stakeholders.
  • Experience in managing high-performance, distributed systems.

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