Applied AI Engineer

sunday•New York, NY

3h•$180 - $220•Hybrid

About The Position

This is one of the most critical hires we're making at sunday right now, and one of the most exciting. As our first Applied AI Engineer embedded within the commercial organization, you'll own the end-to-end AI transformation of how our sales team operates. From pricing intelligence to deal execution to rep-level performance insights, you'll design, build, and ship production AI systems that change the daily reality of our revenue org. You'll report to the GTM Ops Lead and work in close partnership with sales leadership, RevOps, Finance, and the CRO. You're not here to coordinate or project-manage. You're here to build. You'll translate real commercial problems into shipped AI products, with full ownership from ideation to adoption. This is a greenfield role. You're the first person in this function, and you'll set the foundation, the patterns, and the ambition for what AI-enabled commercial execution looks like at sunday. The goal isn't just to ship great work, it's to prove that this function drives meaningful, measurable growth for the business as we scale, and to build a team around it. We'd love for this person to be managing their first direct report within a year or two. If the idea of coming in, working hard, building something from scratch, and growing into a team leader gets you fired up, read on. Join early, grow fast, and shape the journey!

Requirements

5–10 years of experience in GTM, sales, or commercial functions, with at least 2–3 years of hands-on AI build experience, shipping production systems, not just experimenting.
Deep GTM and sales domain knowledge: you understand what a great forecast looks like, how deals move and stall, and what rep-level data actually tells you about performance.
Proven track record of building and shipping AI-powered tools in production - LLMs, prompt engineering, agentic workflows, not just proofs of concept.
Able to operate as a fully independent IC - you scope, build, ship, and iterate without requiring a dedicated engineering team around you.
Strong communicator: you extract requirements from non-technical stakeholders, translate ambiguous business problems into technical designs, and bring teams along with what you build.

Nice To Haves

Experience in the restaurant, hospitality, or payments tech space.
Familiarity with modern GTM automation platforms such as Clay, n8n, Agentforce, or similar agentic tooling.
Experience with data warehouse tooling (Snowflake, BigQuery, dbt) and event-driven systems.
Prior experience as the first AI hire within a GTM or revenue organization.
Proficiency in Python and SQL, with experience working with large commercial datasets.
Familiarity with ML models, data pipelines, or classical data engineering.
Familiarity with the GTM tech stack (Salesforce, Gong, or equivalent).

Responsibilities

Contribute to and influence the AI roadmap for the commercial org, and own its execution: identify the highest-leverage opportunities across the sales motion, help prioritize, and ship production AI systems with pace and precision, from quick wins to foundational infrastructure. The responsibilities below are a starting point, not a ceiling. We expect to define and build new ideas together as this function grows.
Make pricing AI-enabled: build intelligent pricing tooling and workflows that make deal pricing dynamic, consistent, and faster - reducing friction in the cycle and improving win rates.
Automate P&L builds and custom sales decks: design and deploy AI-powered automations that eliminate hours of manual prep, so reps spend time selling, not formatting spreadsheets or building decks from scratch.
Build and own the AI sales forecast: design a robust, AI-driven forecasting system grounded in our actual sales data - giving leadership real-time visibility into pipeline health and revenue trajectory.
Build a sales intelligence bot: ingest and analyze our full commercial dataset to surface actionable, rep-level insights, flagging coaching opportunities, identifying conversion patterns by segment, and helping managers make smarter decisions faster.
Serve as the embedded builder for the GTM team: work directly with AEs, sales managers, and RevOps to understand operational friction and turn their insight into production-ready solutions. No handoffs, no delays.
Establish reusable AI infrastructure: build with scale in mind, creating templates, frameworks, and shared components that will power the next generation of GTM AI products as this function grows.