AI Quality Engineering Lead

Role: AI Quality Engineering Lead – NYC Hybrid

Location: New York, NY 10003
Client: Con Edison
Work Model: Hybrid
Duration: 12 Months
Engagement: Independent Consultant – Must Work on Our Payroll

LOCAL NYC CANDIDATES ONLY – MUST BE ABLE TO INTERVIEW IN PERSON

We are seeking a highly motivated AI Quality Engineering Lead with 8+ years of experience across Quality Engineering, Test Automation, Software Engineering, AI/ML, and Technology Transformation.

This is a hands-on technical leadership role focused on adopting and scaling AI-powered Quality Engineering capabilities across the Testing Center of Excellence (TCoE).

The successful candidate will lead initiatives involving Agentic AI, LLMs, RAG, Multi-Agent Systems, AI-powered testing, and AI-driven engineering accelerators, while establishing enterprise governance, security, Responsible AI practices, and reusable frameworks.

Required Technical Skills

• 8+ years in Quality Engineering, Software Engineering, Test Automation, AI/ML, or Enterprise Technology Delivery
• 3+ years designing and implementing AI/ML, GenAI, or Agentic AI solutions
• Strong Test Consulting, Quality Engineering & Test Automation experience
• AI/ML Solution Architecture and enterprise AI system design
• Strong Python development experience
• FastAPI framework
• LangGraph / LangChain / LLMs
• Agentic AI workflow orchestration
• Prompt Engineering
• RAG – Retrieval-Augmented Generation
• Multi-Agent Systems
• Microservices and API-first architecture
• Event-driven architecture
• Docker and Kubernetes
• DevOps and CI/CD pipelines
• SDLC and AI-enabled software delivery
• Software Architecture and Engineering Transformation

AI & Quality Engineering Responsibilities

• Design and implement scalable enterprise AI solutions for Quality Engineering
• Identify and integrate appropriate LLMs and traditional ML models
• Design data pipelines and integrate AI solutions with enterprise infrastructure
• Develop Agentic AI workflows and multi-agent architectures
• Build RAG-based solutions for engineering and testing use cases
• Develop reusable AI/ML libraries, frameworks, accelerators, and reference implementations
• Establish AI-powered testing and software quality solutions
• Develop prompt engineering strategies and AI solution architecture
• Improve engineering productivity, automation, and SDLC efficiency through AI

Architecture, Governance & Transformation

• Define enterprise AI architecture standards and reusable patterns
• Establish AI governance and Responsible AI practices
• Implement Human-in-the-Loop controls and security standards
• Define engineering governance, operating models, and best practices
• Establish standards for AI-first engineering and software delivery
• Lead enterprise-scale AI adoption and engineering transformation initiatives
• Partner with Engineering, Architecture, DevOps, Security, Product, and Vendor teams

Preferred Skills

• Enterprise Test Automation Framework development
• Reusable automation accelerators
• AI observability and monitoring
• Model evaluation and operational monitoring
• Automated documentation generation
• Release management solutions
• Microsoft Azure AI
• Azure OpenAI
• Azure AI Search
• Cloud-native AI platforms
• Technical consulting and stakeholder management

Education

• Bachelor's degree or higher in Computer Science, Engineering, Information Systems, Data Science, Artificial Intelligence, or related field
• Advanced AI/ML, Cloud, or Architecture certifications are preferred

Candidate Profile

The ideal candidate combines:

Quality Engineering + Test Automation + Python + AI/ML + Agentic AI + LLM + LangGraph/LangChain + RAG + Multi-Agent Systems + Cloud + DevOps + Enterprise Architecture

IMPORTANT: This is a hybrid NYC position. Candidates must currently be local to the NYC area and must be available for an in-person interview.