Applied AI Engineer — Real Estate Tech & Automation

DataJobs; New York (NY); On-site; USD 130,000 - 200,000; Full time

Benefits offered by this job

Health benefits

PTO

Life insurance

401(k) plan

Discretionary bonuses

Equity

Job summary

Blackstone Real Estate in New York is seeking an Applied AI Engineer to turn proprietary real estate information into production-ready AI workflows, including LLM and agent-based solutions. You will work with engineering, data, and security teams to ensure secure, governed deployments and scalable outputs.

Responsibilities include identifying high-impact AI opportunities, building data pipelines and dashboards, and delivering measurable outcomes for investment and operations using Python, SQL,

Qualifications

• 3+ years in software engineering, data engineering, applied AI, or a similar technical role.
• Hands-on experience with Python, SQL, APIs, data pipelines, databases.
• Experience building with LLMs and AI agents, retrieval workflows, automation tools.

Responsibilities

• Collaborate with investment, asset management and teams to identify AI opportunities and deliver deployed solutions.
• Build applied AI systems using real estate data, including dashboards and data pipelines.
• Use Python, SQL, APIs, and databases with LLMs and AI agents to create scalable outputs.
• Coordinate with engineering, data, and security teams to ensure secure, governed deployments.
• Communicate status, risks, and recommendations to technical and non-technical stakeholders.

Skills

Python

SQL

APIs

LLMs

AI agents

Data pipelines

Education

Undergraduate degree in Computer Science or related field

Tools

Databases

Retrieval workflows

Automation tools

Enterprise AI tools

Job description

Blackstone Real Estate in New York is seeking an Applied AI Engineer to turn proprietary real estate information into production-ready AI workflows, including LLM and agent-based solutions. You will work with engineering, data, and security teams to ensure secure, governed deployments and scalable outputs.

Responsibilities include identifying high-impact AI opportunities, building data pipelines and dashboards, and delivering measurable outcomes for investment and operations using Python, SQL,