***PLEASE READ FIRST***
We can not provide sponsorship or work C2C. W2 only.
This is a 6-month contract (with possible extensions) through CDW working for our end client.
Hybrid on-site/remote schedule - 3 days/week work on-site in Lincolnshire, IL, 2 days/week remote work from home
Position Summary:
Client is seeking an AI Engineer Developer to join their Technology & AI Organization. This role sits at the intersection of AI-assisted application development and full-stack engineering. You will take AI-generated front-end prototypes and transform them into production-grade, fully integrated applications—connecting user interfaces to backend services, APIs, databases, and enterprise systems.
You will work across the full software delivery lifecycle—from vibe-coded prototypes built in tools like Lovable and Claude, through GitHub-managed source control, CI/CD via Harness, and deployment to Vercel, GCP, and Azure. This is a hands-on engineering role for someone who thrives at turning rapid AI-generated concepts into reliable, secure, scalable enterprise software.
Key Responsibilities:
Full-Stack Integration of AI-Generated Applications
Take front-end applications generated through AI coding tools (Lovable, Claude Code, Cursor) and extend them into full-stack solutions with backend logic, API integrations, and database connectivity.
Wire up front-end React/Next.js applications to backend services including Supabase (PostgreSQL), Snowflake, Salesforce APIs, and internal microservices.
Implement authentication and authorization flows using Microsoft Entra ID (Azure AD) SSO, OAuth 2.0, and RBAC patterns.
Build and maintain RESTful and GraphQL API layers to connect UI components with enterprise data sources.
AI-Assisted Development Workflow
Operate within client's “Vibe Code” development workflow: Lovable ? GitHub ? Claude Code ? Wiring ? Harness ? Azure/Vercel.
Leverage AI coding assistants (Claude, GitHub Copilot, Gemini Code Assist) to accelerate development while applying engineering judgment to AI-generated output.
Review, refactor, and harden AI-generated code for production readiness—addressing security vulnerabilities, performance concerns, and maintainability.
Collaborate with Agent Developers and AI Solution Architects to integrate AI agent capabilities into applications.
DevOps & Deployment
Manage CI/CD pipelines in Harness for automated build, test, and deployment workflows.
Deploy applications to Vercel (front-end/serverless), GCP (Kubernetes/Cloud Run), and Azure as required.
Implement observability with Dynatrace, including application performance monitoring, log analytics, and alerting.
Follow software supply chain security practices including container image scanning (Chainguard), secrets management (CyberArk), and dependency auditing.
Database & Data Integration
Design and optimize PostgreSQL schemas (with pgvector for AI/embedding workloads) in Supabase.
Build data integration pipelines connecting Snowflake data warehouse to application layers.
Work with Snowflake MCP connectors to enable AI-driven data access within applications.
Ensure data integrity, query performance, and proper indexing across application databases.
API Management & Security
Configure and manage APIs through Kong/Konnect API gateway including rate limiting, authentication, and traffic management.
Implement application security best practices including input validation, prompt injection prevention, and secure coding standards.
Participate in code reviews with a focus on security and quality of AI-generated code.
Required Qualifications:
4+ years of professional software development experience with at least 2 years in full-stack roles.
Strong proficiency in JavaScript/TypeScript, React, and Next.js for front-end development.
Experience with Node.js, Python, or Go for backend/API development.
Working knowledge of PostgreSQL and at least one cloud data platform (Snowflake, BigQuery, or Redshift).
Experience with CI/CD pipelines and modern DevOps practices (GitHub Actions, Harness, Jenkins, or similar).
Familiarity with cloud platforms: GCP, Azure, or AWS (multi-cloud experience preferred).
Experience implementing OAuth 2.0 / SSO authentication flows (Microsoft Entra ID / Azure AD preferred).
Demonstrated ability to read, review, and improve code generated by AI tools.
Strong understanding of RESTful API design, versioning, and documentation.
Comfortable working in Git-based collaborative workflows with branching strategies and pull request reviews.
Preferred Qualifications:
Experience with AI-assisted development tools such as Claude Code, Lovable, Cursor, or GitHub Copilot.
Familiarity with Supabase (PostgreSQL + Auth + Edge Functions) as a backend platform.
Experience with Vercel for front-end deployment and serverless functions.
Knowledge of vector databases and pgvector for AI/embedding workloads.
Experience with Kong or similar API gateway platforms.
Exposure to Kubernetes, Docker, and container orchestration on GCP or Azure.
Understanding of AI agent architectures and how applications interact with LLM-based services.
Experience with Dynatrace, Datadog, or similar APM/observability platforms.
Familiarity with software supply chain security tools and practices (SBOM, image signing, Chainguard).
Background in retail, automotive, or RV dealership technology systems is a plus.