Head of Engineering – AI Platform Transformation

About SimplifyVMS

SimplifyVMS is a leading VMS platform, providing cutting-edge Vendor Management System (VMS) solutions that empower organizations to manage their contingent workforce, direct sourcing, and total talent strategies.

We are a sophisticated multi-tenant SaaS platform built on a MEAN stack (MongoDB, Express, Angular, Node.js) with a mature microservices-based architecture. We are now entering a transformational phase — evolving from a traditional SaaS platform into a fully AI-powered system.

Our goal: refactor and re-architect the platform to integrate generative AI capabilities (e.g., Claude, OpenAI, etc.), enable AI-assisted code generation, introduce automated debugging frameworks, and implement full CI/CD-driven regression and automated testing — within an accelerated 2–3-month timeframe.

We are seeking a hands-on, execution-driven Head of Engineering who has successfully led similar platform modernization or AI-driven refactoring initiatives.

Role Overview

The Head of Engineering will:

- Own the end-to-end technical transformation of the platform - Refactor and modernize a complex microservices MEAN stack system - Architect and implement AI integrations (e.g., Claude or similar LLMs) - Introduce AI-assisted development workflows - Build automated testing (unit, integration, regression) - Establish CI/CD automation - Build and scale the engineering team to support this evolution - Deliver results within an aggressive 2–3 month transformation window

This is not a maintenance role — this is a platform reinvention mandate.

Mission: 90-Day Transformation Mandate

Within 2–3 months, the candidate will:

1. Audit and deeply understand the current platform 2. Identify architectural bottlenecks and technical debt 3. Design a modernization and AI integration roadmap 4. Refactor critical services to support AI augmentation 5. Implement automated testing and regression frameworks 6. Introduce AI-assisted development and debugging workflows 7. Establish engineering velocity improvements 8. Build/augment the team required to sustain the transformation

Key Responsibilities

1. Platform Audit & Refactoring Strategy

- Conduct comprehensive technical audit of: - Microservices architecture - API structures - Data flows - DevOps pipelines - Test coverage gaps - Identify refactor priorities - Redesign components to be AI-compatible and modular - Improve service isolation and performance

2. AI Integration & Augmented Engineering

- Integrate LLM tools (e.g., Claude, OpenAI, etc.) into: - Code generation workflows - Debugging assistance - Intelligent documentation - Refactoring recommendations - Build AI-native services within the SaaS platform - Design guardrails for AI-generated code validation - Create AI-driven observability and issue detection frameworks

3. Automated Testing & Regression Framework

- Implement comprehensive: - Unit testing - Integration testing - End-to-end testing - Regression testing - Establish automated test coverage benchmarks - Embed testing into CI/CD pipeline - Reduce manual QA dependency - Introduce automated code quality gates

4. DevOps & CI/CD Modernization

- Improve build pipelines - Introduce automated deployments - Enable zero-downtime releases - Improve observability and monitoring - Reduce technical debt

5. Team Leadership & Engineering Buildout

- Leverage existing engineering team to accelerate ramp-up - Identify skill gaps and recruit targeted hires - Establish performance standards - Introduce engineering best practices - Build a culture of high-velocity AI-augmented development - Align product and engineering roadmaps

Mandatory Experience Requirements

Candidates MUST have:

- 12+ years of software engineering experience - Experience leading microservices-based SaaS platforms - Deep expertise in MEAN stack (MongoDB, Express, Angular, Node.js) - Proven experience refactoring complex production systems - Experience integrating LLMs or generative AI into engineering workflows - Demonstrated success implementing automated testing frameworks - Experience building AI-assisted development pipelines - Prior experience leading rapid transformation initiatives - Experience building and scaling engineering teams

Candidates without hands-on transformation experience will not be considered.

Highly Preferred Experience

- Experience converting traditional SaaS platforms into AI-enabled platforms - Experience with LLM orchestration frameworks - Knowledge of prompt engineering and AI guardrails - Experience with cloud-native architectures (AWS, Azure, GCP) - Experience implementing observability tools (Datadog, New Relic, etc.) - Experience reducing tech debt in high-growth environments

Leadership Profile

We are looking for someone who is:

- Highly technical and hands-on - Comfortable reviewing code directly - Architecturally strong - Fast-moving and execution-driven - Calm under aggressive timelines - Builder-oriented - Strategic but operationally excellent - Able to inspire and elevate existing teams

Key Success Metrics (First 90 Days)

- AI integration framework live - Refactored core services - 70–80% automated test coverage - CI/CD fully automated - Regression testing in place - Measurable improvement in deployment velocity - Reduced bug backlog - AI-assisted debugging operational - Clear roadmap for ongoing AI-first platform evolution

What This Role Is Not

- Not a maintenance engineering manager - Not a pure architect disconnected from execution - Not a legacy system caretaker

This is a transformation leadership role.

Compensation

- Competitive executive compensation - Performance-based bonus tied to transformation milestones - Equity participation - Executive benefits package

To Apply

Please include:

- Summary of similar transformation you have led - Description of platform complexity handled - Timeline achieved - AI integration experience details - Team size managed - Testing automation frameworks implemented