Portfolio Agile Coach III

  • Location: Chicago, Illinois
  • Type: Contract
  • Job #107186

Principal AI Enablement & SDLC Coach

Insurance Industry | Chicago, IL Preferred (Remote CST/EST Considered)

Location

  • Chicago, IL preferred
  • Remote candidates in CST or EST time zones will be considered for the right experience
  • Long-term contract opportunity with potential for extensions

About the Opportunity

Our client, a leading organization within the insurance industry, is seeking a Principal AI Enablement & SDLC Coach to lead the next evolution of software engineering through AI-native development practices.

This is a unique opportunity for a senior-level technologist who combines deep software engineering expertise with a passion for coaching, organizational transformation, and developer enablement. You will serve as a trusted advisor to engineering teams, helping modernize software delivery by guiding developers from traditional coding workflows toward AI-augmented software orchestration using Claude Code and other emerging AI technologies.

The ideal candidate brings principal-level engineering experience, strong communication skills, and the credibility to engage senior developers, architects, engineering leaders, and executives.


Key Responsibilities

Lead AI Transformation Across Engineering

  • Drive adoption of AI-native software development methodologies across engineering teams.
  • Coach developers on transitioning from manual execution to AI-assisted orchestration and accelerated software delivery.
  • Facilitate formal training sessions, workshops, office hours, and peer-learning communities.

Develop Enterprise Training Programs

  • Design and deliver comprehensive learning paths focused on Claude Code, context engineering, agentic workflows, and AI-assisted development patterns.
  • Build training materials and enablement resources that improve developer productivity while maintaining quality and governance standards.

Design Career Evolution Paths

  • Partner with engineering leadership and stakeholders to define role-specific AI adoption journeys.
  • Help developers understand how responsibilities evolve within AI-augmented engineering environments.

Establish AI Development Standards

  • Educate teams on enterprise AI configurations, including Claude project structures, persistent context management, and reusable skill frameworks.
  • Promote consistent engineering practices and governance-aligned AI usage.

Partner with Engineering Excellence & AI Governance

  • Incorporate security, compliance, governance, and organizational policies into day-to-day developer workflows.
  • Collaborate with architecture, security, and platform teams to encourage responsible AI adoption.

Foster Communities of Practice

  • Build and lead internal communities focused on AI engineering excellence.
  • Create forums that encourage collaboration, knowledge sharing, and continuous learning.

Improve Requirements & SDLC Practices

  • Teach engineering teams how to leverage AI to refine user stories, acceptance criteria, technical designs, and delivery workflows.
  • Advocate for design-first thinking, TDD practices, and automated quality validation.

Promote Cost-Effective AI Usage

  • Guide teams on effective context management, prompt engineering strategies, and responsible token consumption.
  • Help teams balance productivity gains with platform efficiency and governance requirements.

Required Qualifications

Technical Leadership

  • 15+ years of software engineering, architecture, or SDLC leadership experience.
  • Proven success influencing senior engineers, architects, and technical leadership teams.
  • Strong understanding of enterprise software development practices and engineering transformation initiatives.

AI-Native Development Expertise

  • Demonstrated hands-on experience with Claude Code and AI-assisted software development workflows.
  • Experience implementing AI solutions across software delivery lifecycles.
  • Ability to evaluate and improve AI-generated output through structured review, validation, and testing practices.

Full Stack Engineering Background

Strong experience with:

  • Java
  • Spring Boot
  • REST/Web APIs
  • Microservices Architecture
  • Modern relational and NoSQL databases
  • React or other modern SPA frameworks

Coaching & Communication

  • Exceptional presentation, mentoring, and facilitation skills.
  • Ability to communicate effectively with executive, technical, and non-technical audiences.
  • Experience building training programs, mentoring developers, or leading technical enablement initiatives.

Organizational Change Management

  • Experience leading large-scale technology adoption or transformation programs.
  • Ability to support cultural change and drive adoption across engineering communities.
  • Strong emotional intelligence and stakeholder management capabilities.

Quality & Engineering Excellence

  • Strong advocate of Test-Driven Development (TDD), automated testing, and quality-first engineering practices.
  • Ability to teach developers how to validate, refine, and productionize AI-generated solutions.

Enterprise Environment Experience

  • Experience operating within complex enterprise environments with security, governance, compliance, and regulatory requirements.
  • Strong critical thinking and problem-solving skills with the ability to connect technical execution to business outcomes.

Preferred Qualifications

  • Experience with Kubernetes and Docker.
  • Cloud experience in AWS, Azure, and/or GCP environments.
  • Experience integrating AI workflows into CI/CD pipelines.
  • Familiarity with GitHub, GitHub Actions, and modern code quality platforms.
  • Experience developing AI guardrails, custom skills, MCP (Model Context Protocol) servers, or internal AI capabilities.
  • Previous training, coaching, developer advocacy, or technical enablement experience strongly preferred.

Education & Experience

Experience

  • 10+ years of Software Development Lifecycle (SDLC), Architecture, or Engineering Leadership experience
  • 2+ years of AI-native development experience
  • Bachelor's degree in Computer Science, Engineering, Information Technology, or related field preferred
  • Advanced degrees and relevant technical certifications are a plus

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