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 23-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 23 month transformation window

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

Mission: 90-Day Transformation Mandate

Within 23 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
• 7080% 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