Senior Software Engineer, Knowledge Graph/Entity Systems

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
Salary
$119,800–$234,700 / yr
Posted
2 days ago
Closes
Dec 22, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $205k
This role $177k
$104k most similar roles pay here $268k

This role pays less than 70% of similar roles. Most pay $174,637–$235,750 — the shaded band above. At the midpoint, this role pays about $177k versus about $205k for comparable roles.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 694 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 636 roles with salary data.

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At a glance

TL;DR · Senior Software Engineer, Knowledge Graph/Entity Systems

As a Senior Software Engineer on the Entity Data team at Microsoft AI Search, you will be responsible for designing and developing advanced systems that extract, enrich, and understand entities from large-scale content sources using machine learning and LLM-based techniques. Your daily tasks include applying cutting-edge approaches to identify and classify entities, building solutions for entity resolution and linking across multiple data sources, and improving entity quality through rigorous analysis and experimentation. You will work closely with applied scientists, data scientists, and product teams to integrate AI-powered capabilities into production systems while driving technical excellence and mentoring junior engineers. The role requires expertise in software engineering, distributed systems, and experience with large-scale datasets, as well as a passion for solving complex information extraction challenges at scale.

What you'll do

  • Design and develop entity extraction and enrichment systems using machine learning and LLMs.
  • Apply ML techniques to classify and enrich entities from diverse content sources.
  • Build solutions for resolving, disambiguating, and linking entities across data sources.
  • Enhance entity quality through precision/recall analysis and evaluation frameworks.
  • Develop scalable workflows for processing large volumes of structured and unstructured data.

What we're looking for

  • Extensive experience in designing and developing AI-powered entity extraction and enrichment systems.
  • Proficiency in applying machine learning and LLM-based techniques for entity classification and attribute enrichment.
  • Strong background in building scalable solutions for entity resolution, disambiguation, and linking across diverse data sources.
  • Solid understanding of software design, distributed systems, and production engineering practices.
  • Demonstrated ability to independently drive complex projects from concept to production.

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