Principal Engineer - AI Science

When you join Verizon

You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.

What you’ll be doing…

As a Principal Engineer (Agentic & Applied AI), you will serve as a technical leader and individual performer, architecting and driving end-to-end solutions for complex AI and Agentic use cases across multiple concurrent projects. You will be hands-on in design and coding, while leading project pods with one or two junior engineers or data scientists.

• Leading the architecture, design, and end-to-end development of complex Agentic AI and traditional AI/ML solutions across multiple concurrent initiatives.

• Working in a collaborative environment with global teams and managing cross-functional stakeholders across business and technical domains to deliver scalable solutions to high-impact business problems.

• Architecting, developing, and deploying LLM-driven applications, multi-agent workflows, autonomous agent systems, and traditional data science models into production environments.

• Translating complex business requirements into robust technical and system architectures, creating high-level and low-level design documents, and articulating architectural decisions and findings to leadership and stakeholders.

• Hands-on coding and system implementation using Python, LangChain, LangGraph, Model Context Protocol (MCP), REST/gRPC APIs, BigQuery, PostgreSQL, and event-driven architectures with Apache Kafka.

• Guiding, mentoring, and technical coaching of junior engineers and data scientists on project pods—conducting peer code and architecture reviews, sharing constructive feedback, and driving the team toward best-in-class technical execution 

• Designing and implementing robust testing, validation, evaluation, and observability frameworks (e.g., LLM evals, hallucination mitigation, latency/token optimization, model governance) across the end-to-end AI lifecycle.

• Developing next-generation AI systems with built-in data privacy, ethical AI, bias mitigation, guardrails, and compliance with enterprise security and governance policies.

• Assisting in growing the AI practice by leading POCs, identifying new high-value opportunities, defining architectural blueprints, evaluating emerging tools/frameworks, and contributing to technical white papers and documentation.

• Staying informed on the latest advancements in Generative AI, LLMs, Agentic frameworks, and related tech stacks, finding ways to deliver business value by customizing and applying them to our specific enterprise domain.

• Partnering with ecosystem partners, startups, and open-source communities to explore and integrate cutting-edge AI capabilities.

What we’re looking for...

You have deep technical expertise in modern AI engineering and traditional data science, and you thrive as a hands-on technical lead who bridges architecture, coding, and stakeholder collaboration. You are energized by working in a dynamic environment, handling multiple complex projects simultaneously, and translating ambiguous business problems into reliable, production-ready AI systems. You take pride in technical excellence, enjoy mentoring junior team members, and are passionate about advancing state-of-the-art Agentic and LLM architectures within an enterprise scale.

What we're looking for… ("You'll need to have…")

• Bachelor's degree with six or more years of relevant experience.

• Five or more years of hands-on experience in software engineering, applied machine learning, or advanced data science in production environments.

• One or more years of hands-on experience architecting, building, and deploying Agentic AI and LLM-driven solutions (e.g., autonomous agents, multi-agent systems, tool calling/function calling, agent workflows).

• Strong hands-on proficiency with modern AI orchestration and agentic frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent agent frameworks.

• Deep familiarity with Model Context Protocol (MCP) architecture, tool integration standards, REST/gRPC APIs, and microservices design.

• Expert-level coding proficiency in Python and solid software engineering practices (OOP, design patterns, modular architecture, CI/CD, testing, code quality).

• Strong experience working with relational, analytical, and streaming data stores: BigQuery, PostgreSQL, and event-driven architectures using Apache Kafka.

• Solid foundation and working understanding of traditional data science methodologies, predictive modeling, machine learning concepts (supervised/unsupervised learning, neural networks, ensembling), and evaluation metrics.

• Experience with all phases of an end-to-end AI project lifecycle: data ingestion/streaming, preprocessing, prompt engineering/fine-tuning, model validation/evals, containerization, deployment, operationalization, monitoring, and tracing.

• Demonstrated track record of leading technical implementation across multiple simultaneous projects and collaborating effectively with cross-functional business and technical stakeholders.

• Experience providing technical mentorship, conducting architectural and code reviews, and giving feedback to junior engineers and data scientists.

What we're looking for… ("Even better if you have…")

• Master’s degree or PhD in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, or a related quantitative field.

• Experience architecting and deploying AI/ML and Agentic solutions in the Telecommunications domain or large-scale enterprise environments.

• Experience with Vector Databases and advanced Retrieval-Augmented Generation (RAG) techniques (hybrid search, reranking, contextual compression).

• Hands-on experience with LLM evaluation frameworks and guardrail systems 

• Experience with cloud AI platforms (GCP Vertex AI, AWS Bedrock/SageMaker, Azure OpenAI) and distributed compute/data infrastructure.

• Experience in optimization, simulation techniques, or operations research applied to enterprise problems.

• Active contributions to open-source AI projects, agent frameworks, or authoring technical white papers and publications.

• Exceptional presentation, communication, and executive storytelling skills with a proven ability to influence technical and non-technical leadership.

Where you’ll be working

In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.

Scheduled Weekly Hours

40

Equal Employment Opportunity

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.