Sr.AI Engineer

Senior AI Engineer

Plano, TX

12+ Months

Core Software Engineering

• 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.

Cloud & Data Platforms

• 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.

Generative AI & Agentic Systems

• 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:
• Knowledge RAG
• Graph RAG
• Hybrid retrieval systems
• Context-aware retrieval pipelines
• Experience designing enterprise knowledge bases, semantic search solutions, and context-building frameworks.

Large Language Models

• 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.

AI Evaluation & Observability

• Hands-on experience implementing Agentic Evaluation frameworks, including tools such as DeepEval.
• Experience designing evaluation metrics for:
• Retrieval quality
• Hallucination detection
• Answer relevance
• Agent task completion
• Safety and reliability
• Experience with AI observability and monitoring platforms, particularly Arize AI, for production monitoring, tracing, and model performance analysis.

Preferred Qualifications

• Experience with vector databases and embedding models.
• Familiarity with LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar AI orchestration frameworks.
• Experience building enterprise AI applications with governance, security, and compliance considerations.
• Knowledge of MLOps/LLMOps practices, CI/CD pipelines, and model lifecycle management.
• Experience working in Agile product development environments.

Key Responsibilities

• Design and develop scalable AI-powered microservices and APIs using Python and FastAPI.
• Build and maintain enterprise-grade RAG and Graph RAG solutions.
• Develop intelligent agentic workflows that leverage organizational knowledge and business context.
• Optimize knowledge retrieval, context orchestration, and response quality for AI applications.
• Implement evaluation frameworks and monitoring solutions using DeepEval and Arize.
• Deploy, monitor, and maintain AI applications on Azure.
• Collaborate with product, engineering, and business teams to translate use cases into production-ready AI solutions.

Must have existing hands on experience

• Azure AI Foundry
• Azure OpenAI Service
• Semantic Kernel
• LangGraph
• Neo4j or Graph Databases
• Vector Databases (Azure AI Search, Pinecone, Weaviate, Qdrant)
• Kubernetes and Docker
• GitHub Actions / Azure DevOps

This version is targeted at a S Generative AI Engineer (7-10+ years experience).