AI Engineer - NYC

Sequence•New York, NY

2d•$210,000 - $230,000•Hybrid

About The Position

Sequence is building the AI-powered revenue platform for modern finance teams, aiming to replace fragile spreadsheets and legacy systems with software that teams love to use. Companies like Cognition, incident.io, MoonPay, and over 100 other high-growth companies trust Sequence to handle their entire revenue cycle, including quoting, billing, and revenue recognition. The company experienced 10x ARR growth last year and recently closed a $20M Series A funding round led by 645 Ventures, with participation from a16z and other notable investors. Working at Sequence offers a small team environment with significant opportunities and ownership, allowing employees to do impactful work, have direct customer access, and grow with the company. The company is seeking ambitious engineers who take end-to-end ownership of their work, from identification through shipping and customer satisfaction.

Requirements

Shipped LLM-based systems to real customers and have first-hand experience with how they fail in production.
Designed agentic systems and have informed views on the building blocks (embeddings, memory, tool use, long-running state, recovery from partial failures) and when to use each.
Built evals infrastructure (datasets, LLM as judge, prompt regression tests, monitoring) and have a clear view of what good looks like.
Comfortable writing resilient software and respecting the weight of building business-critical systems on top of non-deterministic models.
Informed opinions about the tooling for building, evaluating, and securely running multi-provider AI systems in production.
Experience shipping production backend systems and a focus on reliability.
Customer focus: desire to understand the 'why' behind building something.
Comfort with ambiguity, thriving in early ideation stages, sharing work-in-progress, and adapting based on feedback.
Clear communication skills.
Ability to learn Kotlin, as most of the team learned it on the job.

Nice To Haves

Informed views on which AI tool to reach for and when.
Experience building side projects to explore possibilities.
Serious consideration for AI security, scrutinizing threat vectors and treating models as untrusted by default.

Responsibilities

Build and own the AI infrastructure platform that enables reliable software development on top of non-deterministic models, including agentic workflows, prompt iteration, tools, and evaluations.
Develop AI-powered approval workflows that allow customers to configure flexible routing in natural language, translating these into deterministic, auditable business logic.
Create an intelligent collections agent that can be instructed in natural language to manage the entire workflow of chasing late payments autonomously, including context gathering and escalation.
Contribute to shaping fundamental architecture and shipping features that customers depend on.
Take ownership of problems end-to-end, from identifying needs to ensuring solutions work for real customers.
Build and maintain production backend systems, focusing on reliability.
Understand customer needs and the 'why' behind the work being done.