AI-Native Python Full Stack Engineering

DXC Technology • New Orleans, LA

4d • Hybrid

About The Position

DXC Technology is seeking a hands-on engineering leader to transform Python full stack teams from traditional development practices to an AI-native engineering model. The role will define the strategy, tooling, and organizational changes needed to embed AI agents and copilots throughout the software development lifecycle, from requirements and design through coding, testing, and deployment. The position focuses on redesigning how a Python engineering organization plans, builds, and ships software, treating AI agents as collaborators alongside human engineers and establishing appropriate workflows, quality gates, and skills.

The leader will define an AI-native approach to Python full stack delivery, guide selection and integration of AI development tools, redesign SDLC processes, and establish reusable practices and governance for AI-generated code. They will also enable engineers through training, set quality and security guardrails, measure results, and partner with delivery, account, security, compliance, and client stakeholders to pilot and scale AI-native delivery practices. The work location is flexible, with remote or hybrid work options and a New Orleans, Louisiana location. DXC describes its work model as prioritizing in-person collaboration while offering flexibility.

Requirements

• At least 10 years of software engineering experience.
• Deep hands-on expertise in Python, including Django, FastAPI, or Flask, and full stack development, including React, Angular, or Vue; REST or microservices; and relational and NoSQL data stores.
• At least 3 years in an engineering leadership role, such as architect, engineering manager, or technical director, leading teams of 10 or more engineers.
• Hands-on experience integrating AI coding assistants or agentic tools into real production development workflows, beyond evaluation.
• Strong understanding of modern CI/CD, DevSecOps practices, and cloud-native architecture on AWS, Azure, or GCP.
• Experience designing or redesigning engineering processes or playbooks at scale across multiple teams or a large program.
• Excellent communication skills, including the ability to translate technical AI-adoption strategy into business outcomes for engineering staff and executive stakeholders.

Nice To Haves

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

Responsibilities

• Define the AI-native engineering vision for Python full stack delivery, including target-state workflows, tooling, and an adoption roadmap.
• Lead selection and integration of AI coding assistants, agentic development environments, automated code review, and AI-assisted testing and QA pipelines, ensuring interoperability with existing CI/CD, IDEs, and version control.
• Redesign SDLC processes to incorporate AI agents into requirements decomposition, code generation, test generation, code review, refactoring, documentation, and incident triage.
• Build and lead a center of excellence or working group for AI-native Python development, including reusable prompt libraries, agent configurations, coding standards, and governance for AI-generated code quality and security.
• Develop training curricula and hands-on enablement programs to help developers adopt AI-orchestrated development, including prompt engineering, agent supervision, and review of AI output.
• Establish quality, security, and governance guardrails for AI-generated code, including IP and licensing risk controls, secure coding practices, hallucination detection, and human-in-the-loop review gates.
• Define and track success metrics for developer velocity and throughput, code quality, defect rates, test coverage, cycle-time reduction, and cost-to-serve improvements.
• Partner with delivery leads, account teams, security and compliance teams, and client stakeholders to pilot AI-native delivery on live engagements and scale successful practices.
• Monitor developments in AI coding agents, frameworks, and best practices, and continuously evolve the playbook.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed