Join an AI-native engineering team to develop full-stack AI features for a marketplace, owning projects from inception to deployment, and enhancing AI integration across the platform.
About Our Client
Our client is developing an AI-native marketplace for the purchase and sale of small businesses. They help both owners and buyers move through one of the most significant financial and personal transitions of their lives with clarity, speed, and confidence.
The company is on a strong growth trajectory, with roughly 30,000 buyers and sellers on the platform and more than 100 completed transactions. March was their best month to date (close to $500k in revenue), and April is tracking toward $800k in real banked revenue, with monthly GMV comfortably above $10M. They have raised $15.5M to build a world-class platform, accelerate growth, support more owners, and scale a 30+ person team based in New York City.
AI has driven a step-change in what's possible in this market — and in how the business itself operates. The goal isn't to retrofit AI onto existing workflows; it's to fundamentally re-architect how the product works, how internal operations run, and how value compounds across the platform. Engineers here treat AI as a force multiplier in their own work and in what they ship, and the team takes the craft of production AI seriously.
How AI gets built here: AI systems are shipped to production and operated like any other critical system. Expect to work the full loop — problem framing → data → evals → iteration → deployment → monitoring → continuous improvement — grounded in measurable outcomes (quality, latency, cost, reliability). The emphasis is on shipping quickly and building systems that hold up in the real world.
The team builds in person in NYC because the work moves faster and gets better when everyone is in the room. The culture prizes low ego, high mutual respect, direct communication, and genuine ownership.
Why join: there is real momentum — strong traction, and a set of valuation tools, off-market listings, and a streamlined closing process that are reshaping how small business deals happen at scale. Because the team is still small and lean, every hire has outsized impact: you'll help shape product direction, build core systems end-to-end, and raise the bar on customer-first execution. The work also carries real meaning — when it's done well, it gives small business owners clarity, speed, and confidence at one of the most important financial and personal moments of their lives.
About the Role
Join an AI-native engineering team as a Software Engineer. The engineering org is currently 7 people (a mix of contractors and full-time staff), and everyone is AI-focused. You'll partner directly with the Head of Engineering and the product team to build the AI-native platform powering how small businesses change hands. Your work will directly affect thousands of owners navigating one of the biggest financial moments of their lives.
This is not a papers-and-prototypes role — it's hands-on product engineering with real AI systems. You'll ship full-stack AI projects end-to-end, work closely with sales and operations, and translate real business needs into intelligent product experiences that users engage with every day.
At our client, AI isn't a separate track — it's woven into how products get conceived, built, shipped, and improved. If you're an engineer who thrives on owning the full loop, from identifying the key problem to monitoring it in production, you'll do well here.
Key Responsibilities
⦁ Ship full-stack AI features end-to-end — from scoping with stakeholders to deploying production systems that solve concrete problems for buyers and sellers.
⦁ Own 0-to-1 projects, partnering with sales and operations to find high-leverage opportunities and build intelligent capabilities around them.
⦁ Build and refine the AI infrastructure that supports production-grade inference, evaluation, and monitoring.
⦁ Work across the stack to integrate AI seamlessly into the marketplace, designing clean interfaces that make intelligent features feel native to the product.
⦁ Develop tools and systems that scale — from intelligent matching to document understanding to agentic workflows that reshape how the marketplace operates.
Requirements
⦁ You have shipped and owned production AI systems end-to-end (LLM and/or classic ML) — real users, measurable outcomes, and operational responsibility.
⦁ Strong software engineering fundamentals, excellent Python skills, and proven experience integrating foundation models into production systems.
Bonus Skills
⦁ Hands-on experience with modern AI frameworks (LangGraph, LangChain, LlamaIndex), vector databases, or LLM observability tooling.
⦁ Experience designing evaluation suites for LLM systems (offline and online), including rubric-based and model-graded evals.
⦁ Experience running LLM systems at scale — latency, cost, caching, fallbacks, rate limits, and overall reliability.
⦁ Familiarity with retrieval quality work: chunking, reranking, query rewriting, and relevance tuning.
⦁ A background in marketplaces, platforms, fintech, or small business, with a grasp of matching algorithms or business transactions.
⦁ Familiarity with Go, GraphQL, or React/TypeScript.
⦁ Background in NLP, information retrieval, or recommendation systems.
⦁ Comfort with ambiguity — you do well with limited structure and turn uncertainty into clarity.
⦁ First-principles thinking and genuine intellectual curiosity — you dig into problems from the ground up rather than leaning on established patterns.
Logistics
Location: NYC. 4 days/week in office. Open to relocation.
Compensation: $180–220k + 0.5% equity
Visa Sponsorship: Yes
Interview Process
1. Initial Chat: An introductory screening conversation.
2. Super Day (On-Site): Meet the Co-Founder, CTO, and a Senior Engineer, and complete a case study.
3. Decision: The goal is to reach a decision shortly after the Super Day.
CompensationThe base pay range for this role is $180,000 – $220,000 per year.
Syndesus New York, New York, USA Office
80 Theodore Fremd Ave Rye, New York, United States, 10580
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