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Principal Software Engineer (Python)

Cotality

Irvine, California

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JOB DETAILS
SKILLS
Algorithms, Architectural Services, Artificial Intelligence (AI), Code Reviews, Command Line, Data Science, Ecosystems, Fiduciary, Git, Graph Search, High Availability, Identify Issues, Integration Testing, Knowledge Engineering, Knowledge Representation, Mentoring, Metadata, Metrics, Modeling Languages, Ontology, Performance Tuning/Optimization, Problem Solving Skills, Python Programming/Scripting Language, Real Estate, Relocation Services, Semantic Search, Software Development, Software Engineering, Systems Administration/Management, Technical Leadership, Test Driven Development (TDD), Test Harness, Test Plan/Schedule, Unit Test, Unix Operating Systems, Web Services
LOCATION
Irvine, California
POSTED
Today
At Cotality, we are driven by a single mission-to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society.

Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry.

Job Description:

The hybrid-remote Principal Software Development Engineer leads the design, development, and testing of complex software systems and applications. This senior-level position is responsible for creating scalable, high-quality software solutions while providing technical leadership, driving engineering excellence, and providing mentorship to engineering teams.

The Mission: You will take the helm of our existing Semantic Layer Web Service and lead its evolution into a high-scale, automated intelligence platform. Your mission is to break the current manual bottlenecks-moving the service from 130 manually curated attributes to a system capable of managing thousands. You will bridge the gap between "boutique" internal tools and a fully automated, GraphRAG-enabled enterprise ecosystem.

Job Responsibilities:

  • Architect and Evolve the Semantic Layer: Lead the redesign and scaling of the existing Semantic Layer Web Service, transitioning it from a manual 130-attribute baseline to an automated, high-availability enterprise intelligence platform.
  • Take the Team Anchor Role: Serve as the primary technical lead for the delivery team, owning the architectural vision for Knowledge Representation and Semantic Search while ensuring "fiduciary-grade" performance as the system scales to 1,000+ attributes.
  • Implement Advanced Reasoning: Design and deploy Hybrid Graph/Vector search architectures (GraphRAG) to enable complex global reasoning across disparate enterprise data assets.
  • Develop High-Performance AI Services: Utilize Git or similar, Unix command line, Python, FastAPI, FastMCP, and ADK to build and enhance robust backend services that bridge core enterprise data with Agentic AI.
  • Model Optimization (LLM & SLM): Partner with the Data Science team to architect intelligent routing logic that leverages Small Language Models (SLMs) for high-speed classification/extraction and Large Language Models (LLMs) for complex synthesis.
  • Automate Metadata Ingestion: Collaborate with the Knowledge Engineering team to build automated workflows for Ontology Management and Entity Linking, eliminating single-resource bottlenecks and manual curation constraints.
  • Establish Systematic Evaluation: Collaborate with Knowledge Engineering and Data Science teams to replace "vibe checks" with rigorous automated testing frameworks, utilizing metrics like Faithfulness, Answer Relevance, and Context Precision (RAGAS) to ensure quality during rapid scaling.
  • Conduct Expert Code Reviews: Ensure high code quality, adherence to AI engineering standards, and architectural integrity across the Python/AI stack.
  • Drive Test-Driven Development (TDD): Implement rigorous TDD practices, writing comprehensive unit and integration tests to ensure the reliability of non-deterministic semantic pipelines.
  • Apply Advanced Algorithms: Utilize specialized algorithms for Entity Disambiguation and Ontology Evolution to solve complex knowledge-graph scaling and schema-drift challenges.
  • Optimize Performance and Scalability: Independently plan and execute system optimizations to ensure the Semantic Layer remains performant under enterprise-scale loads and high-dimensional search requirements.
  • Troubleshoot Complex AI Issues: Resolve deep technical challenges related to model hallucinations, "Lost in the Middle" context window phenomena, and retrieval

About the Company

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Cotality

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