AI-Native Java Full Stack Engineering Lead

DXC Technology Inc.; New Orleans, Northern (LA, KY); Hybrid; USD 140,000 - 180,000; Full time

Job summary

DXC Technology is seeking a hands-on engineering leader to transform how Java full stack teams build software with AI-native practices. You will define the strategy, tooling, and governance to embed AI agents and copilots across all SDLC phases, from requirements to deployment.

You will build a center of excellence for AI-native Java, lead modernization of workflows, and upskill engineers in prompt engineering and agent supervision.

Qualifications

• 10+ years of software engineering experience with Java/Spring and full stack delivery.

Responsibilities

• Define the AI-native engineering vision for Java full stack delivery (Spring Boot/Angular, microservices, cloud-native).

Skills

Java

Spring Boot

Full stack development

AI integration

CI/CD

DevSecOps

Cloud-native

AWS

Azure

GCP

Communication

Tools

GitHub Copilot

Cursor

Claude Code

Amazon Q Developer

LangChain

MCP

Job description

Job Description:

We are looking for a hands‑on engineering leader to transform how our Java full stack teams build software, moving them from traditional development practices to an AI-native engineering model. This leader will work with our client to build the strategy, tooling, and cultural shift required to embed AI agents and copilots into every stage of the software development lifecycle, from requirements and design through coding, testing, and deployment. This is not a "add Copilot licenses" role. It's a mandate to fundamentally redesign how a Java engineering organization plans, builds, and ships — treating AI agents as first‑class collaborators alongside human engineers, with new workflows, new quality gates, and new skills to match.

Key Responsibilities

• Define the AI-native engineering vision for Java full stack delivery (Spring Boot/Spring Cloud, Angular/React, microservices, cloud-native architectures), including target‑state workflows, tooling stack, and adoption roadmap.
• Lead tool selection and integration across AI coding assistants, agentic dev environments, automated code review, and AI-assisted testing/QA pipelines — ensuring interoperability with existing CI/CD, IDEs, and version control.
• Redesign SDLC processes to incorporate AI agents at each phase: requirements decomposition, code generation, unit/integration test generation, code review, refactoring, documentation, and incident triage.
• Build and lead a center of excellence (or working group) for AI-native Java development, including reusable prompt libraries, agent configurations, coding standards for AI-assisted output, and governance for AI-generated code quality and security.
• Upskill the engineering workforce, developing training curricula and hands‑on enablement programs to shift developers from traditional coding to AI‑orchestrated development (prompt engineering, agent supervision, code review of AI output).
• Establish quality, security, and governance guardrails for AI-generated code — including IP/licensing risk, secure coding practices, hallucination detection, and human‑in‑the‑loop review gates.
• Define and track success metrics: developer velocity/throughput, code quality (defect rates, test coverage), cycle time reduction, and cost‑to‑serve improvements attributable to AI-native practices.
• Partner cross‑functionally with delivery leads, account teams, security/compliance, and client stakeholders to pilot AI-native delivery on live engagements and scale what works.
• Stay current on the evolving landscape of AI coding agents, frameworks, and best practices, and continuously evolve the playbook.

Required Qualifications

• 10+ years of software engineering experience, with deep hands‑on expertise in Java, Spring Boot/Spring Framework, and full stack development (front‑end frameworks such as Angular or React, REST/microservices, relational and NoSQL data stores).
• 3+ years in an engineering leadership role (architect, engineering manager, or technical director) leading teams of 10+ engineers.
• Demonstrated hands‑on experience integrating AI coding assistants or agentic tools (e.g., GitHub Copilot, Cursor, Claude Code, Amazon Q Developer, or similar) into real development workflows — not just evaluation, but production adoption.
• Strong understanding of modern CI/CD, DevSecOps practices, and cloud‑native architecture (AWS, Azure, or GCP).
• Experience designing or redesigning engineering processes/playbooks at scale (multiple teams or a large program).
• Excellent communication skills — able to translate technical AI‑adoption strategy into business outcomes for both engineering staff and executive stakeholders.

Preferred Qualifications

• Experience in a consulting/services environment, delivering to external clients under contractual SLAs.
• Familiarity with LLM/agent orchestration frameworks (LangChain, MCP, agent‑to‑agent protocols) and prompt engineering best practices.
• Experience establishing governance frameworks for AI‑generated code (security scanning, IP risk, model output validation).

Location: Flexible (Remote/Hybrid — New Orleans,LA)

At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in‑person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.

If you are an applicant from the United States, Guam, or Puerto Rico

DXC Technology Company (DXC) is anEqual Opportunity employer. All qualified candidates will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, pregnancy, veteran status, genetic information, citizenship status, or any other basis prohibited by law. View postings below.

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