Location: Plano, TX (Onsite 3 days/week - local candidates only, no relocation)
Status: Urgent hire - interviewing immediately

Join a global telecommunications technology leader at the forefront of enterprise AI innovation. This is a chance to build production-grade generative AI systems that directly shape how a major organization leverages its knowledge and data at scale.

Why This Role:

You will have the opportunity to architect and ship cutting-edge AI solutions, not just experiment with them. Your work on RAG, Graph RAG, and agentic workflows will move from prototype to production, giving you real ownership and visibility. You will work with a modern, in-demand tech stack and collaborate closely with product, engineering, and business stakeholders, growing your influence as you deliver measurable impact.

What You Will Do:

- Design and build scalable AI-powered microservices and APIs using Python and FastAPI
- Architect enterprise-grade RAG and Graph RAG solutions that power intelligent business applications
- Develop agentic workflows that tap into organizational knowledge and business context
- Optimize retrieval, context orchestration, and response quality across AI applications
- Build evaluation and monitoring frameworks using DeepEval and Arize to ensure AI reliability
- Deploy and maintain AI applications in Azure, owning solutions from development through production
- Partner with cross-functional teams to turn real business use cases into deployed AI products

What You Bring:

Hands-on, production experience with:

- Azure AI Foundry
- Azure OpenAI Service
- Semantic Kernel
- LangGraph
- Neo4j or other graph databases
- Vector databases (Azure AI Search, Pinecone, Weaviate, or Qdrant)
- Kubernetes and Docker
- GitHub Actions or Azure DevOps

Required Skills

Required Skills:

- 8+ years of experience in software engineering with strong expertise in Python.
- Hands-on experience designing and developing microservices-based architectures using FastAPI or similar Python frameworks.
- Experience building scalable, secure, and production-grade APIs.
- Strong experience with Microsoft Azure, including AI, data, and application services.
- Expertise in MongoDB and NoSQL database design, optimization, and data modeling.
- Experience deploying and managing cloud-native applications and containerized workloads.
- Proven experience developing Generative AI solutions using modern LLM frameworks.
- Hands-on experience building AI Agents, multi-agent systems, and autonomous workflows.
- Strong understanding of Retrieval-Augmented Generation (RAG) architectures, including:
1. Knowledge RAG
2. Graph RAG
3. Hybrid retrieval systems
4. Context-aware retrieval pipelines
- Experience designing enterprise knowledge bases, semantic search solutions, and context-building frameworks.
- Strong understanding of Large Language Models (LLMs) and Small Language Models (SLMs).
- Experience with model selection, prompt engineering, grounding strategies, fine-tuning approaches, and inference optimization.
- Familiarity with model performance, latency, cost optimization, and governance considerations.
- Hands-on experience implementing Agentic Evaluation frameworks, including tools such as DeepEval.
- Experience with AI observability and monitoring platforms, particularly Arize AI, for production monitoring, tracing, and model performance analysis.