AI Engineer

About the role

Role: Agentic AI (Telecom is must)

Location: Dallas, TX (Onsite)

Experience: 10+ years

Domain: Agentic AI+Telecom

What You'll Be Doing:

Creating framework applications/features and developing POCs for new feature requests in Verizon's agentic ecosystem.

Owning and driving high-level design, development, business stakeholder engagement, Platform Architecture discussions, and external application team SMEs.

Designing and building agentic platform capabilities across frontend, backend microservices, and AI agent services — including conversational workflows, intelligent intake, content generation, and campaign orchestration.

Leading end-to-end solution design spanning React-based web applications, Java Spring Boot services, Python FastAPI/LangGraph agents, and cloud-native autonomous services.

Building and maintaining RAG pipelines across GCP, Oracle RDS, and PostgreSQL — and owning validation of retrieval quality and agent output accuracy.

Monitoring and comparing agent performance across non-prod and prod environments — latency, accuracy, retrieval quality, and LLM output consistency — to validate readiness before production rollout.

Delivering incremental, production-ready builds with feature flags, safe rollout patterns, and cross-repo coordination.

Setting standards for architecture, scalability, design, and runtime performance — including async agent flows, parallel API integration, RAG optimization, and frontend/backend performance tuning.

Partnering with SRE, platform, AID, and distributed engineering teams (Verizon India and US) to unblock delivery, production changes, and integration with enterprise systems.

What We're Looking For:

Bachelor's degree with 10 or more years of work experience.

Experience with large scale projects.

3 or more years of experience as an Architect or Senior Developer in a large and complex enterprise setting.

Two or more years of specific work experience with building Agentic capabilities.

Strong hands-on experience with Java and Web development technologies — Spring Boot, REST APIs, React, and modern frontend patterns.

Experience working with Microservices architecture and event-driven systems (Kafka, BFF pattern).

Experience with Python agent/AI frameworks (LangChain, FastAPI) and LLM performance optimization.

Hands-on experience with LangGraph (or equivalent agent orchestration frameworks) for building conversational and multi-step agent workflows.

Hands-on experience with RAG development — building retrieval pipelines on GCP, Oracle RDS, and PostgreSQL, embedding strategies, hybrid search, and LLM-grounded knowledge systems.

Ability to own validation of RAG and agent results — accuracy checks, retrieval quality assessment, and output verification before production rollout.

Experience monitoring and comparing agent performance between non-prod and prod — tracking latency, token usage, retrieval hit rates, response quality, and regression across environments.

Experience with Docker containerization and Helm-based Kubernetes deployments.

Strong understanding of end-to-end enterprise application flows — API design, workflow orchestration, data integration, and production deployment patterns.

Ability to work independently on implementations while participating actively in architectural and design discussions.

Certifications (Optional — e.g. GCP/AWS Architect, Kubernetes CKA).

Even Better If You Have:

Experience in the telecom domain and understanding of marketing campaign strategies — offer design, audience targeting, promotional campaigns, and launch planning.

Experience with Adobe Campaign and AEM (Adobe Experience Manager).

Experience with Cloud platforms (GCP, AWS, Cloud Run or equivalent serverless).

Experience integrating with large enterprise systems — catalog/pricing APIs, workflow tools (Jira, Workfront), and content platforms.

Experience coordinating production changes with SRE and cross-region distributed teams.

Excellent communication skills.