AI Infrastructure Engineer

3 weeks, 3 days ago
Full-time
Senior
DevOps and Infrastructure
Umpisa

Umpisa

Umpisa, Inc. partners with industries to drive pioneering solutions through modern software development, aiming to establish the Philippines as a global tech hub.

Internet Software & Services
11-50
Founded 2019

Description

  • Define the AI infrastructure architecture strategy for the platform.
  • Lead cross-functional collaboration with Data Science and Security teams.
  • Design a multi-region GPU cluster strategy.
  • Evaluate emerging AI infrastructure technologies and establish best practices and governance models.
  • Design and implement inference efficiency initiatives such as prompt and context caching.
  • Build systems that provide fine-grained control over cache prefixes and retrieval strategies.
  • Optimize latency and cost efficiency for large-scale LLM inference workloads.
  • Support Retrieval-Augmented Generation (RAG) architectures.
  • Architect and implement end-to-end encryption for cached AI content.
  • Integrate customer-managed encryption keys (CMEK) within cloud environments.
  • Ensure secure multi-tenant data isolation and compliance standards.
  • Develop enterprise-ready vector similarity search systems and scalable embedding search infrastructure.
  • Optimize ANN algorithms for scale and latency.
  • Build ranking models for personalization, recommendation, and monetization.
  • Design and maintain petabyte-scale distributed storage systems with low-latency queries and high-update throughput.

Requirements

  • 5+ years of experience in Infrastructure/Cloud Engineering and IAM.
  • Extensive experience with large-scale distributed systems.
  • Experience leading technical teams.
  • Strong architectural and documentation skills.
  • Knowledge of AI workload optimization.
  • Experience with hyperscale cloud platforms such as Google Cloud Platform.
  • Familiarity with vector databases and ANN indexing techniques.
  • Exposure to LLM inference optimization techniques.
  • Experience building infrastructure that supports generative AI applications.
  • Background in storage engines similar to Google’s Mesa/Napa architecture.
  • Strong systems design skills.
  • Performance optimization mindset.
  • Security-first engineering approach.
  • Experience building enterprise-ready cloud services.
  • Ability to work in high-scale, production-critical environments.
  • Must align with company values including Excellence, Integrity, Professionalism, People Success, Customer Success, Fun, Innovation, and Diversity.
  • Must be a self-starter who enjoys collaborating with teams and clients.
  • Strong communication and problem-solving skills.

Interested in this position?

Apply directly on the company website

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