Senior Engineering Consultant-Cloud & AI

When you join Verizon

You want more out of a career. A place to share your ideas freely even if theyre 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 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 will be doing

The VCP Far Edge Automation team builds and maintains the automation that manages the full lifecycle of Verizons virtualized RAN (vRAN) infrastructure powering the nations largest most reliable 5G network. Alongside our DevOps engineers our AI engineersare responsible for building the intelligent layer of our automation platform: Gen AI agents LLM-powered pipelines and context-aware tooling that reduces manual effort accelerates remediation and makes our automation smarter over time.

As a Senior AI Engineer youll design build and operationalize production-grade Generative AI agents and applications that integrate directly with our automation workflows and network infrastructure. Youll work closely with the team to take technical direction and deliver reliable low-latency AI solutions that the broader team can depend on in production

• Designing developing and deploying production-grade Gen AI agents and applications with a focus on reliability low latency and real-world operability.

• Building and maintaining LangGraph agents and custom Python orchestration logic to power GenAI pipelines enabling low-latency inference context-aware decision-making and multi-step agentic workflows.

• Integrate AI agents with internal data sources Postgres databases and REST API endpoints to give agents the context they needto act intelligently.

• Designing and optimizing data ingestion and preprocessing pipelines in Python to support LLM inference and grounding workflows (RAGtool use structured outputs).

• Collaborating with DevOps engineers to ensure AI agents and pipelines are deployable observable and maintainable within existing CI/CD and infrastructure frameworks.

• Instrument and monitor AI agent performance tracking latency reliability failure rates and accuracy and own improvementsto those metrics.

• Maintaining clear documentation: agent architecture designs integration specs prompt strategies and operational runbooks.

• Staying current with the rapidly evolving LLM and agent tooling ecosystem and bring relevant advances back to the team.

What we are looking for

Youll need to have:

• Bachelors degree or four or more years of hands-on work experience.

• Six or more years of relevant experience.

• Experience with a strong Python focus clean production-grade testable code.

• Deep hands-on experience with the Python ecosystem for AI/ML and data workflows (LangChain LangGraph LlamaIndex or similar orchestration frameworks.

• Demonstrated experience building and deploying LLM-powered agents or applications in a production environment.

• Strong understanding of LLM concepts: prompt engineering RAG tool/function calling context windows structured outputs and agent memory patterns.

• Experience integrating AI systems with relational databases (Postgres or equivalent) and REST APIs.

• Solid understanding of software engineering fundamentals: version control (Git) code review testing and documentation practices.

• Ability to work US Central Standard Time (CST) business hours (8:00 AM to 5:00 PM CT) which corresponds to 6:30 PM to 3:30 AM Indian Standard Time.

Even better if you have:

• Hands-on experience with AI agent frameworks and developer tools such as Claude Code OpenAI Assistants or similar agentic platforms including building custom tooling on top of them.

• Experience with MLOps practices: model versioning pipeline monitoring experiment tracking and production observability for AI systems.

• Familiarity with DevOps tooling Ansible Jenkins GitLab CI and comfort working alongside infrastructure automation engineers.

• Linux server experience and Shell scripting skills for deploying and debugging AI applications in server environments.

• Experience with containerization (Docker Kubernetes) for deploying AI workloads.

• Exposure to telecommunications network operations or infrastructure automation use cases experience applying AI to ops problems like anomaly detection log analysis or failure prediction.

• Familiarity with vector databases (pgvector Pinecone Weaviate or similar) for semantic search and RAG pipelines.

• Experience with streaming or event-driven architectures (Kafka Redis) for real-time AI agent integrations.

If Verizon and this role sound like a fit for you we encourage you to apply even if you dont meet every even better qualification listed above.

Where youll be working

Scheduled Weekly Hours

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.