AI Ops Engineer Mid Level - GTM

Orbital is the AI platform for real estate legal work.

Real estate shapes the world around us: our homes, our workplaces and our cultural landmarks. It’s the infrastructure that powers everyday life and is the world's largest asset class. Yet behind every single deal, real estate and legal teams work hard to navigate decades-old complexity; manually connecting documents, hidden obligations, geo-spatial context, and multiple parties into a path forward. We connect the legal and physical record, so that path is clearer than ever before. Our mission is to make real estate transactions faster, clearer, and less manual.

Here, you'll be part of changing how the deals behind the largest asset class get transacted, and will help shape the future of real estate.

A bit about us:

🚀 We’re building at the forefront of AI technology, without losing the deeply human expertise our clients depend on.

🏢 Orbital is built with former practising real estate lawyers and 250+ years of combined legal expertise. We're purpose-built for the complexity of real estate: accelerating due diligence, drafting and negotiation, and deal coordination with legal-grade precision.

💰 We've just raised a $60m Series B, led by Brighton Park Capital, to accelerate our global expansion – $75m raised to date.

🤝 We're trusted by 5,000+ real estate professionals, spanning UK Magic Circle and US Am Law 100 firms, to household names like M&S. Leading firms like BCLP, Orrick, Goodwin, Womble Bond Dickinson and Clifford Chance rely on Orbital to remove the busywork, freeing legal and real estate teams to focus on sharp judgment, standout client service, and closing deals faster.

💡 Working at Orbital means joining a bold, ambitious team, with the trust to take ownership and make a real impact from day one.

The Role

We're rebuilding Orbital's go-to-market around AI. Not by adding another tool to the stack, but by rethinking how we find, win and grow customers from first principles.

As an AI Ops Engineer (GTM) on our Revenue team, you'll sit with the people doing the work across Sales, Marketing, Customer Success, Product and Finance. You'll question how we work today, reimagine it from first principles with AI, and build what replaces it. You're essentially an internal forward deployed engineer. Over time, you'll help join up the whole business so every team works off the same data and foundations.

The technology is changing every month. We want someone who finds new and unusual ways of doing things, and builds them so they keep working as the tools change.

You'll report to the VP of RevOps. You'll bring a track record of building systems people rely on, and the judgement to decide what to build, what to buy and what to leave alone. We care about what you've built and what it moved, not your job titles.

What you'll do 🎯

• Work alongside teams across the business to understand how they work today, and spot where AI could change the outcome entirely

• Reinvent processes rather than patch them: design and build AI agents, workflows and integrations that change how teams find, win and grow customers

• Connect our systems (CRM, marketing, CS, product and finance data) so every team works from one trusted picture of the customer

• Bring your own ideas, test them quickly with real users, and keep what works

• Ship in short cycles and prove impact. Build the measures that show pipeline created, conversion lift and time saved

• Build things to last: documented, maintainable and easy to adapt as models and tools change

• Share what you learn and help colleagues get more out of AI

• Shape the technical foundations for an AI-forward GTM: how our data, systems and agents fit together across teams

• Make the build, buy or leave-as-is call on new opportunities, and make the case with the expected return

• Set the standards for how we build, including reliability, documentation, data handling and evaluation of AI outputs

What you'll bring 💡

• A track record of building and shipping software, automations or integrations that people used, with the results to show for it

• Strong hands-on experience with LLMs: agents, retrieval, evals or AI-powered workflows in production

• Fluency in at least one programming language (for example Python or TypeScript), plus SQL and third-party APIs

• Experience integrating systems of record such as a CRM, data warehouse or finance tools

• Commercial instincts. You understand how pipeline is created, speak the language of AEs and marketers, and prioritise what moves revenue

• Really smart, curious and proactive: you come with your own ideas rather than waiting for direction

• Evidence of things you've built off your own bat, such as side projects, tools or experiments outside your day job

• Experience working closely with non-technical colleagues to understand their work and build tools they adopt

• Ownership and sound judgement working without a large engineering team around you

Nice to have

• Experience with HubSpot or Salesforce, enrichment tools or GTM data

• Experience at a fast-growing B2B SaaS company

Salary: $150,000 – $180,000 + equity + benefits (New York)

🔒 Security is everyone’s responsibility at Orbital. We ask all team members to follow our security policies, complete regular awareness training, and handle sensitive data with care in line with ISO 27001 standards. Spot something unusual? Reporting risks or incidents quickly helps us maintain the strong culture of security and compliance we all depend on.

💡 At Orbital, we’re committed to building a diverse and inclusive team. We especially welcome applications from people who are traditionally underrepresented in tech. Even if you don’t meet every single requirement, or if the right role isn’t listed yet, we’d still love to hear from you.

💰 This hiring range is a reasonable estimate of the base pay range for this position at the time of posting. Pay is based on several factors, which may include job-related knowledge, skills, experience, and business requirements.

Everyone who works with Orbital goes through background screening before they start. It's part of how we keep Orbital secure, for the people who work here and for the client information we're trusted with.