Distinguished Engineer – AI​/ML Engineering

• Define and drive Verizon's AI engineering, platform, and architecture strategy for Autonomous Network Level 4
• Transform Network Monitoring Center, Network Assurance, and System Performance operations toward autonomous operations
• Lead AI and data engineering teams building agentic AI systems, predictive platforms, and real-time decision engines
• Coach, mentor, assess performance, and set production standards for the AI Engineering team
• Embed generative AI capabilities such as Claude Code into software and prompt engineering workflows
• Partner with network stakeholders to translate operational pain points into agent-driven engineering solutions
• Improve network health signal quality by suppressing alarm noise and eliminating non-actionable tickets
• Deliver automated diagnostic and resolution workflows to reduce mean time to repair
• Engineer self-optimizing network systems, including autonomous network configuration management and self-healing actions across multi-vendor environments
• Define and execute AI software architecture and deployment strategy across the autonomous network lifecycle
• Build anomaly detection pipelines, multi-signal fault correlation, causal root cause analysis, failure prediction, Next Best Action engines, and closed-loop remediation automation

• Bachelor's degree or four or more years of work experience
• Eight or more years of relevant experience, demonstrated through work and/or military experience or specialized training
• Experience in AI/ML engineering, software architecture, and production deployment of large-scale operational systems
• Experience with anomaly detection, time-series forecasting, or fault classification on high-volume telemetry or event data
• Experience building, scaling, and operationalizing real-time AI systems, including anomaly detection and clustering pipelines, root cause analysis services, and Next Best Action recommendation engines
• Experience using multi-dimensional feature engineering
• Experience architecting and deploying end-to-end software pipelines translating operational data into AI models and automated workflows
• Master's degree or PhD in a relevant field (preferred)
• Strong production coding experience with Python, FastAPI, SQL, Kafka, Spark, microservices, and RESTful APIs
• Experience with GCP, Big Query, and streaming data architectures
• Telecommunications network operations expertise, including RAN, Core, or Transport network layers, FCAPS frameworks, network KPIs, and alarm management systems
• Experience designing, building, and deploying Agentic AI systems or multi-agent orchestration frameworks
• Experience using GenAI/LLM tools such as Claude Code
• Demonstrated communication, cross-functional leadership, and stakeholder management skills
• Ability to align technical strategy with business outcomes and resolve executive escalations

Expertise in AI Engineering and Software Architecture, with a focus on building and deploying autonomous network systems and real-time AI solutions. Strong leadership in coaching teams and translating operational challenges into effective engineering strategies.

• AI/ML Engineering
• Anomaly Detection
• Python Programming
• Telecommunications Network Operations
• GenAI/LLM Tools

• AI Engineering
• Software Architecture
• Anomaly Detection
• Time-Series Forecasting
• Root Cause Analysis
• Multi-Dimensional Feature Engineering
• Production Coding
• Real-Time AI Systems
• Automated Workflows Agentic AI Systems

• Communication
• Cross-Functional Leadership
• Stakeholder Management

• Bachelor's Degree
• Master's Degree or PhD (Preferred)

• Telecommunications
• Network Operations
• RAN
• Core Network
• Transport Network
• FCAPS Frameworks
• Network KPIs
• Alarm Management

• Python
• FastAPI
• SQL
• Kafka
• Spark
• GCP
• Big Query
• RESTful APIs