Senior AI Engineer, Agents

Nacre Capital

Every Watch is the largest and most trusted data source in the secondary watch market. Established by a group of watch lovers, Every Watch was created in response to the increasing popularity of luxury timepieces, with the aimof bringing unprecedented transparency and insight to the watch market. The first platform of its kind, Every Watch combines all aspects of the watch world under one roof: a one-stop shop for watch collectors, vendors, and enthusiasts.

We're looking for Senior AI Engineer, Agents - an Agent Architect who will be responsible for designing, building, and scaling AI-powered solutions across Every Watch. Working closely with our engineering, product, sales, and data teams, they will identify opportunities where AI and LLMs can automate complex processes, improve decision-making, and create new capabilities for our users and internal teams.

This is a highly hands-on role for someone who combines strong Python and LLM engineering skills with a creative, proactive mindset. You will not simply be given a roadmap. You will be expected to understand how the business operates, identify where AI can make a meaningful difference, propose new solutions, and take them from idea to production.

Our existing AI work, including Watch Chat, provides a foundation to build on. The opportunity now is to expand that foundation into a broader ecosystem of intelligent agents that can work with Every Watch's unique watch-market data and support collectors, dealers, sales teams, data operations, and engineering.

In short, we're looking for someone who doesn't just ask, "What can we build?" but "What should we build?"

Requirements

• Invent the agent roadmap. Sit with sales, data and product, find the repetitive expert work, and come back with a ranked list of agents worth building - with a real view on feasibility, cost and impact. This is the core of the job, and it doesn't stop after the first quarter.
• Build them yourself. You are hands-on. You design the architecture and you write the code - tools, loops, sub-agents, memory, state, evaluation. Not a spec-writer with a team underneath.
• Own the platform under the agents. Every new agent should be cheaper to build than the last: shared tool layer over Ever Watch data (pricing, auctions, listings, references, portfolios), an MCP surface over our existing backend, shared memory, tracing, and a reusable eval harness.
• Harden Watch Chat alongside us. Multi-turn state and memory, latency, cost, tool-call reliability, regression gates. It's live-bound and it has to stay right.
• Make quality measurable. Golden multi-turn datasets, programmatic verifiers for tool/argument correctness, LLM-as-judge on held-out sets. If we can't measure an agent, we don't ship it.
• Treat cost and latency as design constraints. Cheap models for routing and intent, strong models where they earn their keep; context budgets, caching, and - where it pays off - fine-tuning (SFT/LoRA on curated production trajectories) instead of ever-larger prompts.

Three things, and we won't trade any of them away:

• 6+ years shipping production…