Engineer II - AI/ML Engineering

About the role

Transitioning our enterprise roadmap toward modern agentic AI solutions requires dedicated engineering capability to architect autonomous workflows while establishing enterprise-grade governance and safety guardrails. This role is critical to scaling these complex systems safely, controlling cloud compute costs, and accelerating team delivery velocity across our AI/ML initiatives.

As an AI/ML Engineer (MTS II), you will play a key role in industrializing AI/ML solutions across Verizon. You will collaborate with Enterprise Architecture, Data Science, and Data Engineering teams to build, deploy, and govern scalable machine learning and Generative AI systems across real-time and batch environments.

Responsibilities

• Design End-to-End GenAI & ML Solutions: Architecting and implementing agentic workflows, multi-step Retrieval-Augmented Generation (RAG) systems, and semantic retrieval pipelines for enterprise applications (e.g., personalization, next-best-action, and customer churn models).
• Build Automated Evaluation & Governance Pipelines: Establishing programmatic "evals" to continuously measure model accuracy, latency, hallucination rates, and task performance before and after deployment.
• Production Observability & Monitoring: Implementing enterprise guardrails, tracing, and continuous observability to maintain system uptime, enforce security/privacy standards, and diagnose performance bottlenecks.
• Optimize Cloud & Model Performance: Implementing model routing, prompt/semantic caching, and cost-control strategies across cloud AI platforms (GCP Vertex AI, AWS Bedrock) and self-hosted models.

Requirements

You will need to have:

• Bachelor’s degree or one or more years of relevant work experience.
• One or more years of relevant work experience, demonstrated through one or a combination of work and/or military experience, or specialized training.
• Experience in Machine Learning Engineering, Data Engineering, or Software Architecture.
• Hands-on experience with ML Engineering techniques and tools, including real-time/batch processors and model measurement techniques.
• Hands-on experience with cloud platforms (Google Cloud Platform preferred, or AWS) and modern ML development lifecycles.

Skills

Even better if you have:

• Knowledge of end-to-end Model Development & Management Lifecycles (MLOps/LLMOps), including model inventory tracking, validation, and governance frameworks.
• Hands-on experience with containerized microservices (Docker, Kubernetes) and CI/CD automation tools (Jenkins, GitLab CI).
• Experience designing and implementing agentic workflows, autonomous tool-calling systems, and RAG architectures using vector databases.
• Proficiency in high-concurrency Python programming, FastAPI, PySpark, SQL, Kafka/Pulsar, and Linux/Unix environments.
• Familiarity with enterprise model governance frameworks (bias assessments, Responsible AI standards).

Schedule

In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager.

Scheduled weekly hours: 40

Benefits

Our benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon.

• Health and wellness benefit options including: medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance, and group home & auto insurance.
• Matched 401(k) savings plan.
• Up to 8 company paid holidays per year and up to 6 personal days per year.
• Paid parental leave, adoption assistance, and tuition assistance.
• Other incentives, including premium pay such as overtime, shift differential, holiday pay, and allowances.
• Newly hired employees receive up to 15 days of vacation per year, which grows with additional service.

For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.

Pay

The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive-based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours.

The salary range for the location(s) listed on this job requisition based on a full-time schedule is: $72,000.00 - $129,000.00.