Deployments

AI for the Built World: Build has created the agentic AI stack for institutional real estate, automating complex development and acquisitions workflows 90% faster than humans to accelerate the world's most important built projects - digital infrastructure, energy, industrial - from concept to completion.

Our mission is to accelerate and amplify the world's most important built projects - inventing a better way to build through a collaboration between human experts and agentic AI.

We envision a future where the world's buildings are driven from concept to completion, autonomously. Without delays, cost, and complexity. Enabling people to deliver a magnitude more deals. To make decisions, build relationships and create.

To start, we're partnering with the world's biggest built world institutions from $T alternative assets investors, prolific developers and even governments to push the frontier of what's possible. We're backed by c-suite from Blackstone and OpenAI alongside the world's best venture capital firms.

Join us in shaping the future of the Built World and exponentially accelerate your career in the process. We welcome you to do your life's work here.

We want you to be extraordinary at applying deep built-world judgment inside customer workflows, then using AI to make that work radically faster and more scalable.

This is a Deployments role. You will not be writing production code. You will be the person who carries credible domain depth into live customer environments, decides what good looks like, and turns hard-won expertise into repeatable workflows that agents can run.

You should be energised by the space between domain expertise, customer outcomes and product. Diagnosing how real projects move, judging the quality of agentic output against an institutional bar, and building the workflows that let Build deliver a magnitude more work without losing quality.

You'll own real customer outcomes, and help define what great deployment work looks like at an AI-native company in the built world.

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  Embed with customers to map real development and acquisition workflows, including the constraints, edge cases and failure modes that only show up in live deals

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  Apply expert judgment on the actual work: read the diligence, pressure-test the underwriting logic, assess the entitlement risk and decide what quality looks like

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  Turn domain expertise into structured, repeatable workflows that agentic AI can execute reliably at scale

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  Configure, deploy and iterate on agentic AI systems inside production customer environments, then judge the outputs against an institutional bar

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  Spot where AI meets the messy physical world (zoning, entitlements, financing structures, construction timelines) and design the guardrails that keep outputs trustworthy

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  Close the loop with product and engineering: bring field learnings back as clear requirements, not vague feedback

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  Own customer outcomes end to end: adoption, reliability, speed and the quality of the work delivered

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  Operate independently with high judgment in undefined environments; no playbooks, no guardrails

• Owning a flagship customer deployment end to end: mapping their diligence workflow, configuring the agents, judging the output and getting the team to trust and adopt it

• Turning a messy, expert-led process (site selection, entitlement review, design coordination) into a structured workflow that agents can run repeatably

• Sitting in live deal sessions, identifying where agentic output breaks against an institutional bar and driving the fixes through to shipped improvements

• Validating a new use case or vertical expansion in the field before it is formally productized

• Building the quality framework for a workflow: what good looks like, where it fails and the guardrails that keep it reliable

We're looking for people with real depth across the building lifecycle: development, site selection, diligence, entitlement, design coordination, delivery, operations or infrastructure. You should understand how real projects move, where they break, and what quality looks like to serious institutional customers.

You do not need to be a software engineer. You do need to be AI-native: excellent at structuring messy inputs, judging outputs, designing repeatable workflows, spotting failure modes, and translating domain expertise into processes agents can execute.

• You have credible domain depth across the building lifecycle in REPE, development, infrastructure or a related built-world field

• You've delivered real projects or workflows in an operating capacity and know what institutional quality looks like

• You're AI-native: fluent at structuring messy inputs, judging outputs and designing repeatable workflows

• You have an operator temperament and a bias toward execution

• You're comfortable being the domain authority on-site, earning trust with senior operators and executives

• You move fast, hold a high bar and own outcomes through to completion

• You're energised by ambiguity and care about AI, software and the future of the built world

• You need playbooks and guardrails to operate

• You can run a known process but cannot judge quality or design a new workflow

• You're a generalist without genuine built-world depth

• Prior architecture, design or planning experience alongside your built-world background

• Experience deploying software or new tools into institutional real estate teams

• Experience as a founder, GM or early operator at a high-growth startup

• Existing relationships across REPE, institutional development, infrastructure or energy