Head of Engineering

Reports to: CTO / Chief Product Officer (Founder)

About the Company

A fast-growing AI startup is building an AI-native platform for a large, legacy industry that still relies heavily on manual processes and outdated systems. The company is transforming how businesses in this space sell, support, and operate through AI-powered workflows, automation, real-time communication, and deep system integrations.

Backed by leading investors, the company has already established product-market fit with a growing customer base and is now entering a rapid scaling phase. The platform includes real-time voice capabilities, AI agent orchestration, omnichannel messaging, and complex integrations with enterprise systems.

Why This Role Exists

The founder currently serves as a highly technical CTO and product leader, with extensive engineering experience and strong customer insight. As the company grows, the founder is shifting focus toward customers, product strategy, customer success, and high-level technical direction.

To support this transition, the company is seeking a Head of Engineering to take ownership of day-to-day engineering execution and team leadership.

This is a hands-on leadership role for someone who enjoys both building and leading. You will be responsible for engineering delivery, technical architecture, code quality, and team growth. The CTO will continue setting product direction and supporting the most complex technical challenges, while you ensure that priorities are translated into reliable, scalable software.

Why This Opportunity Is Compelling

This is the company’s first dedicated engineering leadership hire at a pivotal moment. The product is already live, customers are paying, and the next stage is scaling the platform and engineering organization.

You will inherit a functioning product and strong market validation, but have the opportunity to design the engineering organization from the ground up — including team structure, delivery processes, technical leadership layers, and engineering culture.

This role offers a clear growth path toward VP of Engineering as the company continues scaling.

Key Responsibilities

Engineering Ownership

Lead engineering execution across architecture, technical decisions, and delivery. Remain hands-on enough to design complex systems and review critical code rather than operating purely as a people manager.

Team Leadership

Manage, mentor, hire, and grow engineering talent. Structure the organization into focused teams or pods with technical leads across core domains such as AI/Voice, integrations, and platform reliability.

Reliability and Quality

Own operational excellence, including release processes, incident response, observability, on-call practices, and system reliability. A major goal is turning reliability into a predictable strength rather than reactive firefighting.

AI-First Engineering Practices

Drive an AI-native engineering culture where developers leverage coding agents and AI-assisted workflows daily to improve productivity while maintaining high engineering standards.

Cross-Functional Execution

Partner closely with product and design leadership to scope, prioritize, and deliver product initiatives efficiently.

Required Qualifications

• Engineering Leadership Experience:
  Minimum 3+ years managing engineering teams as an Engineering Manager, Head of Engineering, or Director. Strong experience hiring, coaching, retaining talent, and building scalable team structures.
• Strong Technical Depth:
  8+ years building production software with continued hands-on involvement in architecture and implementation.
• AI-Assisted Engineering Expertise:
  Deep familiarity with modern AI-powered development workflows, including coding assistants and agent-based engineering practices. Comfortable using these tools as a core productivity multiplier.
• Reliability Ownership:
  Proven experience managing production systems with real customers, including incident response, service reliability, testing strategies, and operational metrics.
• Backend & Distributed Systems Expertise:
  Strong background in:
  TypeScript / Node.js
  Distributed or event-driven architectures
  Workflow orchestration systems
  PostgreSQL
  AWS cloud infrastructure
  Multi-tenant application design
• Scalability Experience:
  Experience designing and operating high-scale distributed systems, including:
  Event streaming
  Queue management
  Backpressure handling
  Idempotent systems
  Horizontal scaling
  Latency optimization
  Capacity planning
• Infrastructure Architecture Knowledge:
  Able to make high-level infrastructure decisions involving autoscaling, orchestration, observability, and cost-performance tradeoffs while collaborating with DevOps specialists.
• Founder Collaboration:
  Comfortable working closely with a highly technical founder who remains involved in architecture and complex technical decisions.

Preferred Experience

• Real-time voice, telephony, or low-latency communication systems
• AI agent architectures and orchestration frameworks
• Production LLM systems, evaluation pipelines, and model optimization
• Experience in regulated industries such as insurance, fintech, or healthcare

Technology Stack

Backend:
TypeScript, Node.js, NestJS, monorepo architecture

Data & Infrastructure:
PostgreSQL, AWS, infrastructure as code

AI Stack:
Foundation models, prompt orchestration, agent systems, evaluation frameworks, fine-tuned internal models

Frontend:
React, Next.js

Platform & Tooling:
Cloud infrastructure, authentication, observability, CRM/customer success tooling, GitHub, modern delivery tooling

Engineering Principles

• Reliability is essential — production quality is non-negotiable
• AI-first mindset — engineering leverage through AI is expected
• Customer-driven development — prioritize real user feedback over assumptions
• Fast iteration — ship frequently, validate quickly
• End-to-end ownership — engineers own what they build in production

Work Environment

The company operates as a fast-moving distributed team with a strong execution culture. Success depends on moving quickly, staying close to customers, and shipping products that solve real operational problems at scale.