Lead AI Automation Engineer(Agentic Frameworks)
Location: Charlotte, NC or Atlanta, GA (Onsite from day 1)
Duration: 6-12 months
NEED LOCAL ONLY
Job Details:
We are seeking a visionary Lead AI Automation Engineer to spearhead the transition from traditional testing to an AI-infused Software Testing Life Cycle (STLC). You will be responsible for designing and building a proprietary Agentic AI Platform that automates the journey from initial requirements to executable automation scripts.
This is not a role for a prompt engineer; we are looking for a builder who can develop a multi-agent orchestration layer using our internal Large Language Models (LLMs) to redefine quality engineering.
Key Responsibilities:
Platform Architecture: Design and build an Agentic Platform that utilizes specialized LLM agents to handle distinct phases of the STLC.
Agent Development: Develop and fine-tune specialized AI agents, including:
Product Owner Agent: To analyze requirements and draft comprehensive user stories.
Test Lead Agent: To derive complex test scenarios and cases from stories.
Automation Engineer Agent: To automatically generate high-quality Playwright scripts.
Orchestration & Integration: Build the “connected intelligence layer” by integrating the AI platform with ALM tools and Jira.
Technical Leadership: Lead the engineering team through a significant technology and mindset shift, moving away from manual script maintenance toward AI-driven generation.
Framework Evolution: Transition existing automation frameworks into an AI-first ecosystem, ensuring compatibility with tools like Model Context Protocol (MCP) servers.
Required Technical Skills:
AI/ML Engineering: Proven experience building Agentic Workflows and multi-agent orchestration (e.g., LangGraph, AutoGen, or CrewAI).
LLM Implementation: Deep understanding of integrating LLMs into production environments beyond simple API calls, including knowledge of RAG frameworks.
Advanced Automation: Expert-level proficiency in Playwright and modern TypeScript/JavaScript testing ecosystems.
Tooling Expertise: Experience with MCP (Model Context Protocol) and AI-native IDEs like Cursor.
DevOps/ALM Integration: Strong experience with Jira API integrations and ALM (Application Lifecycle Management) software.
Preferred Qualifications:
Experience building custom AI tools that review user stories or perform static analysis on requirements.
A background in migrating legacy testing frameworks to modern, AI-augmented architectures.
The ability to articulate a clear technical roadmap for AI-infused testing that spans the entire SDLC.
Contact Information
Email: harman@hmgamerica.com
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