Founding Engineering Lead

Founding Engineering Lead

Location: New York, NY Work Arrangement: On-site, 5 days per week Employment Type: Full-time Experience: 5–12 years Base Salary: $250,000–$350,000 Equity: Competitive equity Visa Sponsorship: Open to visa transfers and sponsorships, including OPT, H-1B, and TN

Company Description

We’re working with an early-stage enterprise software company building an AI-powered platform that helps businesses improve how they manage and grow existing customer relationships.

The platform combines structured customer data, machine learning, and AI agents to help companies identify important customer signals, prioritize opportunities, and determine the right actions to drive retention and expansion.

The company is building in a large and evolving area of enterprise software, with a focus on turning complex customer data into actionable insights and automated workflows.

You’ll join a small, high-performing team at an important stage of product development. As the Founding Engineering Lead, you’ll work closely with the technical leadership team, own major architectural decisions, and help take the product from early traction toward a scalable, self-serve platform.

This is a hands-on technical leadership role for an engineer who enjoys building, shipping, and mentoring others. You’ll spend approximately 75% of your time writing code and 25% providing technical leadership, with a clear opportunity to grow into a Head of Engineering or VP of Engineering position.

What You Will Do

Product Engineering & Execution

• Build and ship product enhancements end to end, helping move the platform from founder-led delivery toward a scalable, self-serve product.
• Own important product and engineering initiatives, from technical design through implementation and deployment.
• Work across the full stack, with a stronger focus on backend engineering and data-heavy systems.
• Build reliable, scalable systems that support increasingly complex customer workflows and product capabilities.
• Take ownership of technical problems and drive solutions independently.

Technical Architecture & Engineering Leadership

• Own key technical architecture decisions and help evolve the existing platform alongside the CTO.
• Identify opportunities to improve system architecture, engineering practices, performance, and scalability.
• Build custom development workflows and harnesses that use AI agents to increase engineering productivity.
• Explore multi-agent orchestration and AI-native development practices to improve how the engineering team builds and ships software.
• Lead and mentor a small engineering pod of approximately 2–3 engineers.
• Contribute to sprint planning, technical scoping, code quality, and engineering standards.
• Gradually take on broader people-management responsibilities as the team grows.

Applied ML & AI Systems

• Contribute to the technical and product roadmap, particularly around applied machine learning and AI-driven workflows.
• Work with the team on longer-term initiatives involving custom model training and agentic pipelines.
• Apply machine learning fundamentals to real-world product problems involving structured customer data.
• Develop informed technical perspectives on LLMs, transformer architectures, and the practical use of AI in production systems.
• Help identify opportunities to use AI agents and machine learning to improve product capabilities and engineering velocity.

Ideal Candidate Background

• 5+ years of software engineering experience, ideally within the 5–12-year range.
• Strong full-stack engineering experience, with a backend lean and hands-on experience building data-heavy or applied AI products.
• Strong proficiency in Python and experience working with modern frontend frameworks such as React and Next.js.
• Comfortable working across the stack, including backend services, APIs, frontend applications, and data-intensive systems.
• Deeply AI-native, with practical experience using AI agents and building custom agent-driven development workflows.
• Experience with multi-agent orchestration or advanced AI-assisted engineering workflows.
• Strong applied machine learning fundamentals, including classical ML algorithms and data science workflows.
• Ability to discuss LLM training, transformer architectures, and the trade-offs involved in building AI-powered products.
• Currently hands-on and actively shipping code. This is not a purely managerial position.
• Has no more than approximately three years of experience in purely management-focused roles.
• Previous experience mentoring engineers, leading technical projects, or guiding a small engineering team.
• Strong ownership mentality and the ability to operate independently in a fast-moving startup environment.
• Based in or willing to relocate to New York City and comfortable working on-site five days per week.

Technical Skills

Backend & Full-Stack Engineering

• Python.
• Node.js.
• React.
• Next.js.
• API development and backend architecture.
• Data-heavy application development.
• End-to-end product engineering.

Applied Machine Learning & AI

• Classical machine learning algorithms.
• Applied ML and data science workflows.
• Large Language Models (LLMs).
• Transformer architectures.
• AI agents and agentic workflows.
• Multi-agent orchestration.
• Model training concepts and evaluation.

AI-Native Development

• AI-assisted software development.
• Custom development harnesses.
• Agent-driven coding workflows.
• Multi-agent development systems.
• Tools and workflows that improve engineering productivity.

Cloud & Infrastructure

• Google Cloud Platform (GCP).
• Scalable backend systems.
• Production application architecture.
• Data infrastructure and integrations.

Preferred Background

• Experience at an early-stage startup or high-growth technology company.
• Previous experience as a founding engineer, technical lead, or early engineering hire.
• Experience building applied AI products or products that use machine learning in production.
• Experience working with customer data platforms, enterprise SaaS, revenue operations, or business intelligence products.
• Experience building AI agents, agentic workflows, or multi-agent systems.
• Experience designing custom development tools, internal engineering platforms, or AI-powered coding workflows.
• Experience mentoring engineers and leading a small engineering team.
• Familiarity with GCP and modern cloud infrastructure.
• Experience contributing to technical roadmaps and making architectural decisions alongside founders or CTOs.

Leadership & Working Style

• Hands-on leadership: Enjoys writing code and building products while providing technical direction to others.
• High ownership: Comfortable taking responsibility for major engineering decisions and delivering outcomes independently.
• AI-native mindset: Actively explores and uses AI agents and new development workflows to improve engineering productivity.
• Strong technical judgment: Can make thoughtful decisions around architecture, scalability, maintainability, and product trade-offs.
• Mentorship: Enjoys helping engineers improve through technical guidance, code reviews, and collaboration.
• Startup mentality: Comfortable operating in a small team where priorities evolve and individuals have significant ownership.
• Product orientation: Understands how engineering decisions translate into customer value and business outcomes.
• Execution-focused: Can move quickly without compromising the quality and reliability of the product.

Compensation & Benefits

• Base Salary: $250,000–$350,000.
• Equity: Competitive equity.
• Work Arrangement: On-site, five days per week.
• Location: New York City.
• Visa: Open to visa transfers and sponsorships, including OPT, H-1B, and TN.

The company is willing to offer above-market cash compensation and equity for exceptional candidates.

Why Join?

• Founding-level ownership: Play a central role in shaping the engineering organization and the technical direction of the product.
• Build and lead: Spend most of your time building while mentoring a small engineering team.
• AI-native engineering: Work with AI agents and custom development workflows to push engineering productivity forward.
• Shape the architecture: Work directly with technical leadership on important system design and architecture decisions.
• Influence the product