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AI Integration Architect

Cotality

Austin, Texas

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JOB DETAILS
SKILLS
Application Programming Interface (API), Architectural Design, Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Authentication, Cloud Applications, Continuous Deployment/Delivery, Continuous Integration, Cost Engineering, Database Design, Defense in Depth, Economics, Ecosystems, Error Handling, High Throughput, Input/Output, Insurance, MCP - Microsoft Certified Professional, Memory Hardware, Metadata, Real Estate, Risk, Risk Analysis, Security Architecture, Software Design, Software Engineering, Standards Development, Telemetry, Underwriting, Unstructured Data, User Interface/Experience (UI/UX), Workflow Analysis
LOCATION
Austin, Texas
POSTED
2 days ago
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:

About Cotality

Cotality is the insurance industry's leading provider of property intelligence, risk analytics, and workflow solutions. Our data powers underwriting, claims, and catastrophe risk decisions for the nation's largest carriers. We are building the AI-first data foundation that defines how the industry consumes property intelligence, and this role sits at the center of that transformation.

Role Summary

We are looking for a Senior AI Architect to design and deliver AI systems across Cotality's property intelligence platform. This is a hands-on individual contributor role with broad scope spanning internal agentic systems that power property analytics and decision workflows, and external AI integration architecture that makes Cotality's data products consumable by AI agents, foundation model platforms, and enterprise developer ecosystems.

You will work across both layers, ensuring they are coherent, secure, and built to scale with the growth of our product portfolio. You will define the standards, build the foundational components, and be accountable for the architecture working in production under real client load.

Key Responsibilities

Technical
  • Design and build agentic AI systems, including multi-agent frameworks, orchestration layers, memory and retrieval architectures, and tool-based reasoning pipelines that operate against structured and unstructured property data.
  • Own the external AI integration architecture, API gateway configuration, MCP server patterns, authentication and authorization flows, tool schema standards, and the reference architecture that product teams follow to expose their APIs as agent-consumable tools.
  • Pioneer Agent Experience (AX) design as a first-class methodology for the organization analogous to UX or Developer Experience (DX). Treat AI agents as primary consumers of our systems and ensure that APIs, tool descriptions, and data outputs are optimized for LLM comprehension, context limits, and deterministic reasoning.
  • Establish and enforce technical standards for how AI agents consume Cotality's data products, with a focus on tool description quality, input and output contracts, error handling patterns, and response metadata standards all evaluated through the lens of AX.
  • Architect security and data provenance controls across the integration layer, including JWT claim schema design, defense-in-depth authorization patterns, audit logging, and response boundary enforcement.
  • Design and implement observability and telemetry for AI systems to monitor token consumption, latency, error rates, prompt drift, LLM costs, and response quality in production.
  • Establish CI/CD pipelines and evaluation frameworks for AI agents that measure accuracy, hallucination rates, and performance regressions before changes reach production.
  • Optimize AI workload architecture by designing deployment strategies that decouple large model weights from application code, utilizing optimized base images and dynamic runtime mounting to maintain fast, reliable CI/CD pipelines.
  • Scale inference and orchestration by architecting high-throughput AI backends using specialized model servers such as vLLM or Triton on Kubernetes, with support for dynamic batching, streaming responses, and concurrent execution.
  • Align application design with cloud economics by partnering with platform engineering to build cost-aware AI systems, and designing agentic workflows that gracefully handle cold-start latencies and infrastructure scaling events such as scale-to-zero or Spot instance evictions without dropping requests.
  • Bring strong

About the Company

C

Cotality