Verizon
Verizon
„Verizon“ yra telekomunikacijų bendrovė, teikianti vartotojams, įmonėms ir valdžios organizacijoms belaidžio ryšio, plačiajuosčio interneto, šviesolaidinių tinklų ir susijusias skaitmenines paslaugas. Jos veikla apima mobiliąją ir fiksuotojo ryšio infrastruktūrą, mažmeninės prekybos bei internetinius kanalus ir įmonių komunikaciją, todėl galimybių atsiranda tinklo technologijų, klientų aptarnavimo, verslo sprendimų ir kitose srityse, padedančiose užtikrinti didelės apimties ryšį.

Senior AI/ML Engineering Consultant – Verizon, Chennai Hybrid

Lead Verizon’s enterprise AI governance engineering, from secure deployment pipelines to production LLM observability. Build agent gateways, compliance integrations, and automated controls for large-scale AI systems.

Aprašymas

  • Lead an engineering pod through the build and operational phases of Verizon’s end-to-end AI governance ecosystem
  • Define the architecture connecting AI development platforms with safety and compliance hubs
  • Establish enterprise AI governance standards and align guardrails with Legal, InfoSec, and Responsible AI teams
  • Convert manual governance reviews into automated workflows with approvals completed within the same session
  • Design and implement deployment pipelines that apply Security, Responsible AI, Integrity, and Legal controls
  • Develop advanced agent simulations using the Tau2 benchmark
  • Deploy continuous, real-time telemetry for production large language models
  • Create APIs linking developer platforms with Verizon governance hubs, including Engram and Agent Registry
  • Design identity, access management, and routing controls in the Agent Gateway to secure autonomous workflows
  • Advance applied research through intellectual property, patents, and improved evaluation metrics

Reikalavimai

  • A bachelor’s degree or at least six years of professional experience
  • At least five years of relevant experience gained through professional work or specialized training
  • Strong expertise in deploying AI solutions across different architectural patterns
  • Ability to optimize GPU cluster usage and compute-credit spending through strategic resource planning
  • Experience applying AI and machine learning governance practices in enterprise environments
  • Preferred: strong knowledge of AI and generative AI architecture and distributed systems
  • Ability to address AI governance, security, Responsible AI, integrity, and legal controls
  • Experience building APIs, IAM and routing logic, and observability for production LLM systems
  • Experience with agent simulation and evaluation frameworks, including Tau2 benchmarking

Privalumai

  • Hybrid work arrangement with designated work-from-home days
  • Office attendance scheduled by the manager

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