Senior AI Native Full Stack Engineer

Senior AI-Native Full-Stack Engineer

AIDLC / Forward-Deployed Delivery

Location: Minnesota; local candidates required

Role Overview

We are seeking a senior full-stack engineer who uses AI coding agents as the primary method of software development. This is not a traditional keyboard-first or backend-focused role. The engineer will direct tools such as Codex, GitHub Copilot, Claude Code, and enterprise-approved ChatGPT to design, build, test, document, and deliver production software.

The role emphasizes user-facing application development, AI-native delivery, Agile execution, and close collaboration with business stakeholders. The engineer should also be comfortable operating in a lightweight Forward Deployed Engineer (FDE) capacity—turning ambiguous business needs into prototypes, specifications, working software, and production-ready solutions.

Required Skills and Attributes

• 7 years of professional software engineering or software delivery experience
• 4 years of full-stack application development experience, with an emphasis on modern user experiences and end-to-end feature delivery
• Demonstrated production use of AI development tools such as Codex, GitHub Copilot, Claude Code, or comparable coding agents
• An AI-first development mindset, using agents for implementation rather than relying primarily on manual coding
• Ability to create specifications, provide effective context, decompose work, review generated output, and redirect AI agents when results are incomplete
• Strong experience with React, Angular, or a comparable modern front-end framework
• Proficiency with JavaScript ES6 , TypeScript, HTML, and CSS
• Working experience with middle-tier services, including REST APIs, application integration, data access, and service orchestration
• Familiarity with Java 17 , Spring Boot, or comparable middle-tier technologies; deep backend specialization is not required
• Experience with relational or NoSQL databases such as PostgreSQL, MySQL, Oracle, or Cosmos DB
• Experience with Azure, AWS, or Google Cloud and automated CI/CD delivery
• 5 years delivering software in Agile or Scrum environments
• Ability to translate business outcomes into stories, acceptance criteria, specifications, and AI-executable tasks
• Strong stakeholder communication, facilitation, demonstration, and problem-solving skills
• Ability to validate AI-generated solutions for functionality, security, performance, maintainability, and architectural fit
• Must be located in Minnesota and available for local collaboration as required

Preferred Skills and Attributes

• Experience with specification-driven or agentic delivery methods such as Spec Kit, BMAD, reusable agent instructions, or multi-agent workflows
• Experience rapidly prototyping solutions and incorporating stakeholder feedback
• Experience with Docker, Kubernetes, automated testing, observability, and production support
• Experience in enterprise-scale or regulated environments
• Familiarity with secure and responsible enterprise AI usage

Primary Responsibilities

1. Deliver full-stack capabilities using AI-native development practices

Including user interfaces, middle-tier services, integrations, data access, tests, documentation, and deployment assets.

2. Operate in a mini-FDE role

Work directly with stakeholders to discover needs, create prototypes, demonstrate solutions, gather feedback, and support adoption.

3. Own Agile delivery from discovery through production

Including refinement, planning, specification development, incremental delivery, demonstrations, and release support.

4. Review and validate AI-generated software

Correct outputs when necessary and ensure solutions meet enterprise quality, security, accessibility, and maintainability standards.

5. Improve the AIDLC operating model

By creating reusable specifications, prompts, instructions, test patterns, context files, and delivery practices.

Preferred Background

Experience in enterprise application or product development, consulting, professional services, modernization, or customer-facing solution delivery is preferred.

Healthcare, insurance, financial services, SaaS, or another regulated industry is beneficial.

The ideal candidate is a full-stack, AI-first problem solver who can move comfortably between business discovery, user experience, middle-tier integration, prototyping, implementation, demonstration, and production delivery.

Manual coding should be used selectively for validation, debugging, and complex exceptions—not as the default development approach.