# AI Engineer (Assistant)

**Company:** [Build](https://hotfix.jobs/companies/build-inc)
**Location:** New York, NY, London, United Kingdom
**Role:** ML Engineering
**Salary:** $125k – $225k/yr
**Skills:** Python, LLM APIs, Agent Frameworks, Structured Outputs, Tool Calling, RAG, Document Processing, Workflow Systems, LangGraph, LangChain, Temporal, Vector Databases, Multimodal Models, Observability
**Posted:** 2026-08-29

> Build and ship production agentic AI workflows for complex real estate and built-world processes. The role combines product engineering, applied AI, customer collaboration, workflow orchestration, evaluation, and reliable user-facing experiences.

## Job Description

## Responsibilities
- Design and ship production AI workflows for real estate design, acquisitions, diligence, planning, and project execution.
- Work with customers and domain experts to map complex workflows into software systems with clear inputs, outputs, edge cases, and success criteria.
- Build agents that reason across leases, zoning documents, site plans, drawings, financial models, market comps, investment memos, permits, emails, and project history.
- Own full-stack product features from backend workflow logic through user-facing review, approval, and collaboration surfaces.
- Design context strategies for documents, prior decisions, domain constraints, tool outputs, and user intent.
- Build retrieval, extraction, structured-output, and tool-calling flows for expert users.
- Create evaluations for document understanding, grounded reasoning, workflow completion, visual QA, accuracy, latency, and customer usefulness.
- Inspect traces, debug failures, improve prompts and workflows, and convert customer feedback into measurable system improvements.
- Partner with AI and infrastructure teams on agent reliability, observability, evaluation, and developer velocity.
- Build inspectable, explainable, and trusted AI systems.

## Requirements
- Strong product-minded software engineering background with production systems used by real users.
- Experience building with LLM APIs, agent frameworks, structured outputs, tool calling, retrieval-augmented generation, document processing, or workflow systems.
- Proficiency with Python and modern backend systems, with the ability to work across the stack.
- Ability to translate ambiguous customer problems into reliable products.
- Understanding of evaluations, traces, regressions, edge cases, latency, cost, and user trust.
- Comfortable collaborating with domain experts and learning complex industries.
- Strong product judgment and an ability to make complex AI behavior understandable.

## Nice-to-haves
- Experience with LangGraph, LangChain, Temporal, workflow engines, vector databases, reranking, document AI, multimodal models, or agent observability tools.
- Experience building AI products in real estate, construction, infrastructure, finance, legal, insurance, logistics, or other expert-heavy domains.
- Experience designing human-in-the-loop systems, review workflows, confidence surfaces, or expert feedback loops.
- Experience turning customer-specific workflows into reusable product capabilities.

## Compensation and Benefits
- Meaningful equity.
- Significant ownership of customer and product problems.
- Opportunity to work on agentic AI, product engineering, and institutional real estate.

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