Verizon
Verizon
Verizon is a telecommunications company serving consumers, businesses, and government organizations with wireless connectivity, broadband, fiber-optic networks, and related digital services. Its operations span mobile and fixed-line infrastructure, retail and online channels, and enterprise communications, creating opportunities for professionals working across network technology, customer services, business solutions, and other functions supporting large-scale connectivity.

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.

Description

  • 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

Requirements

  • 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

Benefits

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

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