AI Ops Engineer (GTM)
Orbital
New York, United StatesFresher3h agovia LinkedIn
This job at a glance
- Who can apply
- New grads, no experience needed
- Must know
- MarketingREST APIsLLMsPythonJavaScriptSQL
- Nice to have
- CRMSalesforceSales
- Work
- On-site in New York
- Pay
- Not stated by the employer.
- Skill demand
- Python77%LLMs65%REST APIs58%Marketing2%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 6, 2026 · still open
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About the Role
Orbital is rebuilding its go-to-market strategy around AI. As an AI Ops Engineer (GTM) on the Revenue team, you will question current processes, reimagine them with AI, and build the solutions. You will act as an internal forward-deployed engineer, helping to integrate the entire business onto a unified data foundation. The role is for someone early in their career with exceptional raw ability and a strong capacity for learning. You will report to the VP of RevOps.
Key Responsibilities
- Embed with revenue teams to understand workflows and identify opportunities for AI and automation.
- Build AI agents, workflows, and integrations to reduce manual work and improve decision-making.
- Connect systems (CRM, marketing, CS, product, and finance data) to create a unified customer view.
- Experiment with new approaches, test them with users, and retain successful solutions.
- Ship in short cycles, measure impact (e.g., pipeline created, conversion lift, time saved).
- Build documented, maintainable, and adaptable solutions for evolving models and tools.
- Share knowledge and help colleagues leverage AI effectively.
Requirements & Tech Stack
- AI Agents
- LLM APIs
- AI Coding Tools
- Python
- JavaScript
- SQL
- APIs
- CRM (HubSpot or Salesforce)
- Automation Tools (n8n, Zapier, or Make)
Qualifications
- Strong academic background in a quantitative or technical subject (e.g., computer science, engineering, maths, physics, economics) or equivalent evidence of exceptional ability.
- Clear evidence of building projects (side projects, tools, automations, GitHub repositories, startup experience, hackathons, or work-related accomplishments).
- Hands-on experience building with AI, including LLM APIs, agents, or AI coding tools.
- Some coding ability in languages such as Python, JavaScript, or SQL, and comfort working with APIs.
- Exceptional problem-solving skills: ability to break down complex issues, learn quickly, and articulate thinking clearly.
- Commercial instincts: understanding of pipeline creation, ability to communicate with Sales and Marketing teams, and prioritize revenue-driving activities.
- Comfort with ambiguity and a strong sense of ownership in a fast-moving team.
- Nice to have: Time in a customer-facing, sales, or consulting role.
- Nice to have: Experience with a CRM (HubSpot or Salesforce) or automation tools like n8n, Zapier, or Make.
- Nice to have: Experience at an early-stage or fast-growing startup.