Engineering Manager – Modernization & AI Enablement

Engineering Manager – Modernization & AI Enablement

Location: Remote
Role Type: Full-Time
Reports To: CEO

The Opportunity

Sched is a profitable event management platform ($5M ARR, targeting $15M+). We are evolving our engineering organization by blending strong technical leadership with modern, AI-assisted development practices.

We seek an Engineering Manager capable of guiding a small team through the challenges of a 15+ year legacy system while driving the transition toward an efficient, AI-enabled future. This senior role requires hands-on technical understanding, leadership skills for setting standards, and the ability to partner across the business. If you excel at modernizing systems, improving engineering workflows, and coaching engineers to leverage modern tools, this role is an excellent fit.

The Mission

Your primary mission is to significantly increase engineering throughput and product reliability without requiring a linear increase in headcount. This will be achieved by combining:

• Clear technical leadership
• Structured modernization work
• Pragmatic use of AI-assisted development tools (e.g., Copilot, Cursor, Claude, Replit)

The goal is to make development work faster, safer, and more predictable.

First 30 Days: Establish Reality

The initial focus is mapping the system before accelerating development. In your first three months, you will:

1. Assess the current PHP codebase and infrastructure.
2. Identify legacy areas, high-risk sections, and key modernization priorities.
3. Document technical debt clearly for business actionability.
4. Define where AI tools can realistically speed up documentation, refactoring, and testing efforts.
5. Establish a predictable development workflow that effectively blends human judgment with AI output.
6. Build a phased modernization plan executable alongside normal product work.

This foundational work prepares the company for its next stage of growth.

Key Result Areas

1. Engineering Leadership & Team Development

• Lead and coach a small engineering team, setting clear expectations.
• Help engineers effectively adopt and utilize AI tools.
• Build a culture emphasizing accountability, continuous learning, and ownership.
• Focus on hiring, retaining, and developing strong talent.

Outcome: A team that ships predictably, works collaboratively, and uses modern tooling with confidence.

2. Technical Delivery & Modernization

• Improve the health of the legacy PHP system through structured cleanup and documentation.
• Reduce technical debt in a prioritized, business-aligned manner.
• Utilize AI tools for code explanations, prototypes, tests, and refactors.
• Collaborate with Product to scope work realistically and unblock roadmap items.

Outcome: A more stable, understandable system resulting in fewer surprises and faster delivery cycles.

3. Reliability, Observability & Security

• Strengthen logs, monitoring, and alerting systems.
• Partner with Business Operations to ensure the secure use of AI tools.
• Reduce incident frequency and improve time-to-resolution metrics.
• Maintain strong on-call and incident management practices.

Outcome: Higher reliability and a more predictable customer experience.

4. Cross-Functional Collaboration

• Work closely with Product teams to align on scope, sequencing, and priorities.
• Partner with Sales and Customer Success to understand customer needs and unblock revenue streams.
• Plan around Schedmin and other internal tools to ensure product work, back office workflows, and data remain synchronized.
• Identify opportunities where automation or lightweight middleware can solve problems faster than core engineering efforts.
• Communicate technical tradeoffs clearly to business partners.

Outcome: Engineering becomes a trusted, proactive partner to every team.

Core Requirements

• Experience leading engineers in a SaaS environment (1–3 years is beneficial if IC background is strong).
• Strong technical foundation in PHP or similar web stacks.
• Proven experience modernizing or refactoring legacy systems.
• Comfortable jumping into code when necessary.
• Deeply integrates AI into daily engineering workflows, making it a default part of design, coding, review, and communication processes.
• Clear, proactive, and direct communicator who surfaces risks early, thinks upstream, and translates impact for internal and external users.
• Strong prioritization, sequencing, and tradeoff skills; ability to clearly explain execution timelines and rationale.
• Bias toward action and iterative improvement.