Associate Architect

2 days ago


Bengaluru, Karnataka, India Quantiphi Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Role :
Associate Architect - MLOps / LLMOps

Experience :
6 to 8 Years

Location :
Bangalore / Mumbai (Hybrid)

Job Summary:

Join our dynamic team as a
Platform Architect
and leverage your expertise in production-scale platforms within the
GenAI or ML domain
. In this role, you'll be instrumental in designing, developing and maintaining cutting-edge build and test environments for critical GenAI workloads running on foundational cloud infrastructure.

You'll partner with architects to design and implement highly robust and scalable systems, while also providing crucial development support to SRE/Operations teams as they tackle complex distributed systems challenges at scale. We're seeking an engineer who champions Quantiphi's dedication to
Cloud-Native development
, with a particular emphasis on
Kubernetes
.

Job Responsibilities:

As a
Platform Architect
, you will play a pivotal role in designing, implementing, and optimizing our cutting-edge infrastructure. Your responsibilities will include:

  • Designing and implementing state-of-the-art GPU compute clusters
    to support critical workloads.
  • Designing comprehensive automated testing strategies and frameworks
    across unit, integration, API, and end-to-end levels for critical commerce flows.
  • Developing robust performance testing frameworks
    to validate platform scalability, resilience, and identify optimization opportunities.
  • Planning of comprehensive monitoring solutions
    with alerting systems to track platform health and ensure SLA compliance.
  • Designing specialized test frameworks for security controls
    and ensuring compliance validation across payment and personal data.
  • Architecting a scalable automation infrastructure
    that supports growing platform capabilities with consistent test environments.
  • Troubleshooting, diagnosing, and performing root cause analysis
    of system failures, isolating components and failure scenarios in collaboration with internal and external partners.
  • Optimizing cluster operations
    for maximum reliability, efficiency, and performance.

Job Requirements:

We are seeking a highly skilled and passionate
Platform Engineer
with:

  • Over 6-8 years of experience working with developing ML Infrastructure.
  • Over 3 years of hands-on experience
    in large-scale
    direct experience building and deploying production-ready services on Kubernetes.
  • A proven history of
    engaging with and contributing to open-source projects
    .
  • A
    collaborative spirit
    , demonstrated by prior work developing scalable software solutions for cloud services.
  • The ability to
    effectively communicate complex technical designs and quality approaches
    across various mediums.
  • A
    deep understanding of GPU computing and AI infrastructure
    .
  • A strong
    passion for solving complex technical challenges
    and optimizing system performance.
  • Working knowledge of cluster configuration management tools
    such as BCM or Ansible, and infrastructure-level applications including Kubernetes, Terraform, and MySQL.
  • In-depth understanding of container technologies
    like Docker and Containers.
  • Proficiency in programming with Python and Bash scripting.

Ways To Stand Out From The Crowd:

Candidates who possess the following will be highly competitive:

  • Significant experience with sophisticated infrastructure tooling
    , including Kubernetes Cluster API, Terraform, Helm, and Operator Framework.
  • Practical, production-level experience across major cloud platforms
    : Azure, Google Cloud Platform (GCP), or Amazon Web Services (AWS).
  • Ability to adapt to new technologies and Frameworks in ML/GenAI landscape.
  • A strong track record of
    successfully refactoring and optimising software for deployment within Kubernetes environments
    .
  • Comfort discussing and working with
    core Kubernetes concepts like CSI, CNI, and CRI
    .
  • Comprehensive understanding of the CNCF landscape
    and its associated tooling.
  • The ability to
    decompose complex problems into simpler sub-problems
    and leverage existing solutions for efficient implementation, along with designing simple, self-sustaining systems.
  • Experience leveraging
    AI/ML to proactively detect and resolve incidents
    , automate alert triaging, perform log analysis, and streamline repetitive workflows.


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