AI Engineer

Phaxis; Nashville (TN); Hybrid; USD 243,560,000 - 272,214,000; Full time

Job summary

Phaxis is seeking an experienced architect to lead the architecture and hands-on development of Azure-based GenAI, agentic automation, and enterprise integration solutions.

You will design GenAI solutions with LLM orchestration, prompt engineering, RAG, grounding, tool calls, evaluation frameworks, guardrails, confidence handling, and human-in-the-loop controls. You will own the Azure AI and integration layer for ServiceNow AI BPO, with secure APIs, data mappings, and governance.

Qualifications

• Experience with Azure GenAI and enterprise integration
• Strong understanding of cloud AI services and security controls
• Familiarity with Python and REST APIs

Responsibilities

• Lead architecture and hands-on development of Azure-based GenAI, agentic automation, and enterprise integration solutions using Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Azure SQL, Cosmos DB, and related services.
• Design GenAI solutions using LLM orchestration, prompt engineering, RAG, grounding, tool/function calling, evaluation frameworks, guardrails, confidence handling, and human-in-the-loop controls.
• Own the Azure AI and integration layer supporting ServiceNow AI BPO solutions, including secure APIs, data mappings, asynchronous processing, error handling, logging, monitoring, and operational fallbacks.
• Establish GitHub-based engineering standards covering branching, pull requests, code reviews, CI/CD, testing, work-item traceability, release controls, and technical governance.
• Implement AI security, quality, and operational controls covering prompt injection, data leakage, responsible AI, managed identity, secrets management, private networking, monitoring, tracing, cost, and performance.

Tools

Azure AI Foundry

Azure OpenAI

Azure AI Search

Azure Functions

Azure SQL

Cosmos DB

Job description

Pay rate is $85 to $95 per hour
3 days onsite and 2 days remote

• Lead the architecture and hands-on development of Azure-based GenAI, agentic automation, and enterprise integration solutions using Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Azure SQL, Cosmos DB, and related services.
• Design GenAI solutions using LLM orchestration, prompt engineering, RAG, grounding, tool/function calling, evaluation frameworks, guardrails, confidence handling, and human-in-the-loop controls.
• Own the Azure AI and integration layer supporting ServiceNow AI BPO solutions, including secure APIs, data mappings, asynchronous processing, error handling, logging, monitoring, and operational fallbacks.
• Establish GitHub-based engineering standards covering branching, pull requests, code reviews, CI/CD, testing, work-item traceability, release controls, and technical governance.
• Implement AI security, quality, and operational controls covering prompt injection, data leakage, responsible AI, managed identity, secrets management, private networking, monitoring, tracing, cost, and performance.
• Use Python, REST APIs, JSON, event-driven patterns, and cloud-native services to build scalable enterprise AI and automation solutions while reviewing vendor-developed code for security, quality, and architecture alignment.