AI Ops Engineer (GTM) - Mid Level

Orbital•New York City, NY

About The Position

Orbital is rebuilding its go-to-market around AI. The AI Ops Engineer will join the Revenue team as an internal forward deployed engineer, working with Sales, Marketing, Customer Success, Product, and Finance to understand existing processes and build AI-driven systems that improve how the company finds, wins, and grows customers. The role will help connect teams through shared data and foundations, and shape the technical architecture for an AI-forward go-to-market function. The successful candidate will build and integrate AI agents, workflows, and systems; assess opportunities to build, buy, or leave processes unchanged; and prove the impact of shipped work. Systems should be reliable, documented, maintainable, and adaptable as models and tools evolve. The role reports to the VP of RevOps.

Requirements

A track record of building and shipping software, automations, or integrations that people used, with demonstrable results.
Strong hands-on experience with LLMs, including agents, retrieval, evaluations, or AI-powered workflows in production.
Fluency in at least one programming language, such as Python or TypeScript, as well as SQL and third-party APIs.
Experience integrating systems of record such as a CRM, data warehouse, or finance tools.
Commercial instincts and understanding of how pipeline is created; ability to communicate with account executives and marketers and prioritize work that moves revenue.
Curiosity, proactivity, and ability to bring forward ideas without waiting for direction.
Evidence of independently built projects, tools, or experiments, including outside the day job.
Experience working closely with non-technical colleagues to understand their work and build tools they adopt.
Ownership and sound judgment when working without a large engineering team.

Nice To Haves

Experience with HubSpot or Salesforce, enrichment tools, or go-to-market data.
Experience at a fast-growing B2B SaaS company.

Responsibilities

Work with teams across the business to understand current processes and identify where AI could significantly improve outcomes.
Design and build AI agents, workflows, and integrations that transform how teams find, win, and grow customers.
Connect CRM, marketing, customer success, product, and finance systems so teams share a trusted view of the customer.
Develop ideas, test them quickly with users, and continue with approaches that work.
Ship in short cycles and measure impact, including pipeline created, conversion lift, and time saved.
Build documented, maintainable systems that can adapt as models and tools change.
Share learnings and help colleagues make better use of AI.
Shape the technical foundations for an AI-forward go-to-market function, including how data, systems, and agents work across teams.
Evaluate new opportunities and recommend whether to build, buy, or leave them as-is, making the case based on expected return.
Set standards for reliability, documentation, data handling, and evaluation of AI outputs.