Principal, Software Development Engineering

Principal Engineer

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.

This role is responsible for shaping backend architecture, driving cross-team technical strategy across our global engineering workforce, and ensuring the scalability, correctness, and operational excellence of critical location-based platforms, address standardization systems, and high-throughput Web APIs. Operating with broad scope and influence, the Principal Engineer partners closely with engineering leaders, product teams, and enterprise stakeholders across insurance, real estate, and telecommunications domains to align technical outcomes with business priorities.

Additionally, this role will lead greenfield technical initiatives, including the development of Model Context Protocol (MCP) servers to expose core location data capabilities to AI-powered workflows and applications.

Key Responsibilities

Technical Leadership & Architecture

• Own and evolve the architecture of core Location Services, address standardization platforms, and geospatial API capabilities.
• Architect and implement MCP (Model Context Protocol) servers to enable seamless, AI-driven access to backend location data and customer use cases.
• Define standards for consolidating legacy address-standardization implementations into scalable, unified platform architectures.
• Mentor senior and mid-level engineers, strengthening overall technical capability

Platform Ownership & Delivery

• Guide technical initiatives across mixed-language stacks (Python, Java, C, .NET) and distributed cloud environments.
• Partner with product and engineering leaders to balance legacy platform maintenance with greenfield AI development initiatives.

Cross-Team Influence

• Provide technical direction, code quality standards, and architectural guidance across a hybrid engineering structure including global contractor teams (US, Vietnam, India, Mexico).
• Resolve cross-cutting technical dependencies for downstream enterprise consumers across insurance, real estate, telecommunications, and financial verticals.

Job Qualifications:

Required Qualifications

• 10+ years of professional software engineering experience with demonstrated senior or principal-level technical leadership.
• Strong hands-on engineering background with proficiency in one or more core stack languages:
  Python, Java, C,
• Deep experience designing, building, and operating large-scale distributed systems, spatial data models, geospatial queries, and Web APIs.
• Experience building and operating cloud-native services (AWS, GCP, or Azure).
• Proven ability to guide architecture, establish implementation plans, and lead technical execution across distributed teams without direct line management authority.

Preferred Qualifications

• Familiarity with Model Context Protocol (MCP) server development or integrating backend microservices into LLM/AI workflows.
• Domain experience in insurance, real estate, mortgage, telecommunications, aerospace, or Esri-based technology ecosystem.
• Direct experience with address standardization algorithms, location accuracy platforms, or real-time spatial processing pipelines.
• Experience utilizing AI developer tooling (Git Hub Copilot, Gemini) and spec-driven development frameworks.

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