Overview

As the Engineering Lead for AI Email Applications at Next Steps Systems, you own the engineering layer that turns AI capability into a reliable product. You will shape the architecture across backend services, APIs, and client applications while leading a small team of senior engineers. This is a hands-on leadership role where you stay close to the code, make critical architectural decisions, and ensure the system remains fast, reliable, and coherent as it scales.

This position is 100% remote.

Note: Candidates must be willing to take a 60-minute coding assessment.

Responsibilities

• •Own the application engineering strategy and execution across backend, mobile, and desktop.
• •Design reliable systems for AI-powered workflows, including state, orchestration, tool use, retries, fallbacks, and failure handling.
• •Build the APIs and abstractions that connect AI systems to real-world product experiences.
• •Lead a small, senior engineering team and raise the technical bar through design reviews, code reviews, and hands-on mentorship.
• •Make high-impact trade-offs across latency, reliability, cost, security, and user experience.
• •Establish strong production foundations: observability, monitoring, testing, and operational excellence.
• •Partner closely with ML leadership to turn model capabilities into robust, shippable product experiences.
• •Move quickly while keeping the architecture simple, maintainable, and ready to scale.

Outcomes

• •Production systems are observable, monitored, and stable under real-world load.
• •Decisions consistently balance speed, cost, reliability, and user experience.
• •Features across backend, mobile, and desktop work smoothly and reliably.
• •Latency and reliability improve measurably over time.

Qualifications

• •AI experience is required.
• •Significant experience leading application or product engineering for complex systems.
• •Strong hands-on background building and shipping backend systems used in production.
• •Experience building AI-powered products or systems that integrate with modern ML/LLM capabilities.
• •Strong technical judgment and the ability to make decisions with incomplete information.
• •Comfortable working across backend and client platforms, with deep expertise in at least one.
• •A strong bias toward ownership, shipping, and learning from real-world usage.
• •High standards for code quality, reliability, and engineering fundamentals.

Benefits

• •Medical insurance
• •Dental and vision coverage
• •Savings plan options
• •Paid time off (PTO)