ML/Backend Engineer — LLM-Powered Analytics & Data Trust

Link Logistics Real Estate Holdco LLC; New York (NY); Hybrid; USD 140,000 - 155,000; Full time

Benefits offered by this job

Health insurance

Retirement savings plan

Paid holidays

Paid time off

Job summary

Link Logistics Real Estate is seeking a hybrid ML/Backend Engineer to own the intelligence layer of Link's Analytics Engine. You will design knowledge graphs, build retrieval pipelines, and develop LLM-driven investment analytics workflows.

The role requires 4+ years in ML/backend engineering, strong Python, and experience with data provenance. You will work with investment teams to deliver low-latency, reliable ML outputs and APIs.

Qualifications

• 4+ years in ML engineering, backend engineering, or a role spanning both.
• Hands-on experience shipping LLM-powered applications in production - RAG pipelines, prompt engineering, eval frameworks.
• Strong Python skills; comfortable owning backend services and APIs end-to-end.
• Experience with knowledge graphs or graph databases (Neo4j or similar).
• Proficiency building data pipelines at scale (Spark, Databricks, or equivalent).
• Deep sensitivity to data provenance - a track record of building systems that create analyst trust, not just claim it.

Responsibilities

• Knowledge Graph & Retrieval - Design graph-based data structures encoding relationships across markets, assets, tenants, and transactions.
• Build retrieval pipelines (RAG, hybrid search, structured queries) that give LLMs accurate, contextually rich grounding.
• LLM Workflow Automation - Develop rule-based and agentic LLM workflows that automate investment analytical tasks. Own prompt engineering, eval frameworks, and production reliability.
• Data Pipelines - Build ETL/ELT workflows that ingest, normalize, and enrich large-scale internal and third-party datasets (property records, leasing data, macro signals, alt data).
• Data Trust & Provenance - Build systems that make data trustworthy by design: lineage tracking from source to insight, confidence scoring on derived outputs, and clear attribution so analysts always know where a number came from and how fresh it is.
• Backend API Layer - Develop and maintain APIs and services that expose ML outputs and structured data to front-end applications. Prioritize low-latency, reliability, and clean contracts with the application team.
• Collaboration - Work directly with investment and asset management teams to understand analytical needs and iterate quickly.

Skills

Python

LLM systems

Backend APIs

Knowledge graphs

Spark/Databricks

Tools

Neo4j

Databricks

Spark

Job description

Link Logistics Real Estate is seeking a hybrid ML/Backend Engineer to own the intelligence layer of Link's Analytics Engine. You will design knowledge graphs, build retrieval pipelines, and develop LLM-driven investment analytics workflows.

The role requires 4+ years in ML/backend engineering, strong Python, and experience with data provenance. You will work with investment teams to deliver low-latency, reliable ML outputs and APIs.