Job Title: Solution Lead Enterprise Java, GenAI & AI-Powered Engineering

Location: Plano, TX
Experience: 12 15 Years
GenAI/Agentic AI Experience: 2 3+ Years
Work Arrangement: Hybrid 3 Days Onsite per Week
Duration: 12 Months (NO BENEFITS)

Job Overview

We are seeking an experienced Solution Lead with strong expertise in Enterprise Java architecture, Generative AI (GenAI), Agentic AI, and AI-powered software engineering. The ideal candidate will have a proven track record of designing scalable enterprise applications, particularly in commerce environments, and leveraging AI-driven development tools to accelerate software delivery while maintaining high standards of quality.

This is a hands-on, customer-facing technical leadership role requiring expertise in Java enterprise architecture, large language models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and modern AI development frameworks.

The Solution Lead will collaborate with customers, business stakeholders, architects, and engineering teams to drive AI transformation initiatives, lead solution design, deliver proofs of concept (PoCs), and guide teams in adopting AI-assisted software development practices.

Key Responsibilities

1. GenAI and Agentic AI Architecture

• Design and implement enterprise-grade GenAI, RAG, and Agentic AI solutions.

• Lead engagements from discovery and architecture through PoC, MVP, and production deployment.

• Evaluate LLMs, AI frameworks, vector databases, and cloud-based AI services.

• Integrate AI capabilities into enterprise applications, commerce platforms, and business workflows.

• Implement prompt engineering, embeddings, function calling, and AI agent orchestration.

• Apply AI security, responsible AI practices, guardrails, and observability to enterprise AI solutions.

2. Enterprise Java Architecture

• Provide technical leadership in Java enterprise application development using Java 11/17+, Spring Boot, REST APIs, and microservices.

• Design scalable distributed systems and event-driven architectures.

• Lead architecture discussions, technical design reviews, and code reviews.

• Establish engineering standards, reusable design patterns, and best practices.

• Support legacy application modernization using cloud-native technologies and AI-assisted development approaches.

• Ensure enterprise applications meet performance, scalability, security, and reliability requirements.

3. AI-Powered Software Engineering

• Demonstrate hands-on expertise with AI development tools such as Windsurf, Cursor, GitHub Copilot, Claude Code, OpenAI Codex, or equivalent agentic development environments.

• Drive AI adoption across the software development lifecycle, including requirements analysis, coding, testing, code reviews, documentation, and modernization.

• Identify opportunities to automate repetitive engineering tasks and improve developer productivity.

• Establish best practices for AI-assisted coding, validation, testing, and code quality.

• Measure and improve engineering efficiency through AI-enabled development practices.

4. Customer Engagement and Solution Delivery

• Conduct customer workshops, discovery sessions, and architecture discussions.

• Collaborate with business and technical stakeholders to understand requirements and define scalable solutions.

• Translate business challenges into practical enterprise architecture and AI implementation strategies.

• Support solution proposals, technical estimations, proof-of-concept development, and executive presentations.

• Communicate technical concepts effectively to business stakeholders and engineering teams.

• Drive solution delivery with a strong focus on quality, ownership, accountability, and business outcomes.

5. Technical Leadership and Innovation

• Mentor architects, senior developers, and engineering teams on Enterprise Java, GenAI, Agentic AI, and AI-assisted development.

• Lead technical reviews and guide teams in adopting modern engineering practices.

• Participate in hackathons, innovation initiatives, and rapid prototyping activities.

• Develop reusable accelerators, frameworks, and AI-enabled engineering assets.

• Promote collaboration across architecture, development, and delivery teams.

Required Qualifications

Enterprise Java

• 12 15 years of experience in software engineering, app