Senior AI Engineer

Senior AI Engineer
Contract
Dallas, TX onsite

Role Overview

We are seeking a Senior AI Engineer to architect and deploy autonomous AI systems. You will move beyond simple chatbots to build Agentic Workflows that can plan, execute tasks, and retrieve complex data. This role requires deep expertise in the Azure AI ecosystem, specifically in orchestrating multi-agent systems and optimizing Retrieval-Augmented Generation (RAG) using vector databases.

Key Responsibilities

*1. Agentic AI & Orchestration

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Design and implement multi-agent architectures using frameworks like Microsoft Semantic Kernel, AutoGen, or LangGraph to solve complex, multi-step business problems.

Build autonomous agents capable of tool calling (function calling) to interact with internal APIs, databases, and third-party SaaS platforms.

Implement state management and memory persistence to allow agents to maintain context across long-running sessions.

1. Advanced RAG & Vector Search

Architect high-performance RAG pipelines using Azure AI Search or Cosmos DB for vector storage.

Optimize retrieval accuracy using Hybrid Search (Keyword Vector) and Semantic Re-ranking strategies to reduce hallucinations.

Design data ingestion pipelines that handle chunking, embedding (e.g., Ada-002/003), and metadata filtering for enterprise-scale knowledge bases.

1. Azure AI Infrastructure

Deploy and manage models via Azure AI Foundry (formerly AI Studio) and Azure OpenAI Service, ensuring proper quota management and content filtering.

Integrate AI services with Azure Functions and Logic Apps to trigger agent actions based on real-time events.

Ensure enterprise security compliance (RBAC, Private Endpoints) within the Azure cloud environment.

Technical Requirements (The "Must-Haves")

Core AI Stack:

Generative AI: Deep experience with Azure OpenAI (GPT-4o, GPT-3.5) and open-source models (Llama 3, Mistral).

Vector Databases: Hands-on production experience with Azure AI Search (formerly Cognitive Search), Cosmos DB for MongoDB (vCore), Pinecone, or Qdrant.

RAG Architectures: Proven ability to build "GraphRAG" or "Agentic RAG" systems, not just simple document Q&A.

Agent Frameworks:

Proficiency in Semantic Kernel (C# or Python), AutoGen, or LangChain/LangGraph for orchestration.

Cloud & DevOps:

Azure Native: Experience with Azure AI Foundry, Azure Machine Learning (AML), and Azure Functions.

Programming: Expert-level Python (FastAPI, Pydantic) (for enterprise Semantic Kernel integration).