AI Ops Engineer (GTM) - Junior

Orbital•New York, NY

2d•$100,000 - $120,000

About The Position

Orbital is rebuilding its go-to-market operations around AI. The AI Ops Engineer (GTM) will join the Revenue team as an internal forward-deployed engineer, working alongside Sales, Marketing, Customer Success, Product, and Finance to understand existing processes and redesign them using AI and automation. The role will help connect business systems and data so teams can work from a shared, trusted view of the customer. The position is intended for someone early in their career with exceptional ability. Orbital prioritizes learning speed and evidence of things built over years of experience or job titles. The engineer will experiment with changing AI tools, test solutions with users, ship in short cycles, demonstrate measurable impact, and create maintainable, documented systems that can adapt as models and tools evolve. The role reports to the VP of RevOps.

Requirements

Strong academic background in a quantitative or technical subject, such as computer science, engineering, mathematics, physics, or economics, or equivalent evidence of exceptional ability.
Clear evidence of building, such as side projects, tools, automations, a GitHub portfolio, a startup, hackathon work, or things shipped at work.
Hands-on experience building with AI, such as LLM APIs, agents, or AI coding tools.
Some coding ability, for example in Python, JavaScript, or SQL, and comfort working with APIs.
Exceptional problem-solving ability, including breaking down messy problems, learning quickly, and explaining thinking simply.
Commercial instincts, including understanding how pipeline is created, speaking the language of account executives and marketers, and prioritizing work that moves revenue.
Comfort with ambiguity and a strong sense of ownership in a lean, fast-moving team.

Nice To Haves

Time in a customer-facing, sales, or consulting role.
Experience with a CRM such as HubSpot or Salesforce, or automation tools such as n8n, Zapier, or Make.
Experience at an early-stage or fast-growing startup.

Responsibilities

Embed with revenue teams to understand their work and identify where AI and automation could improve outcomes.
Build AI agents, workflows, and integrations to remove manual work and support better decisions.
Connect CRM, marketing, customer success, product, and finance systems so teams can use a trusted, shared picture of the customer.
Try new approaches, test them quickly with real users, and continue with what works.
Ship in short cycles and demonstrate impact by measuring pipeline created, conversion lift, and time saved.
Build documented, maintainable solutions that are easy to adapt as AI models and tools change.
Share learnings and help colleagues make better use of AI.