Principal, AI Engineering

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:

We are seeking a highly motivated and self-driven AI Engineer with a strong background in building scalable Gen AI/Agentic AI data engineering solutions. The ideal candidate brings deep expertise in Google Cloud Platform (GCP), with hands-on experience in Gen AI/Agentic AI Engineering, Google Doc AI, BigQuery, Postgres and Python. Familiarity with Data Engineering technologies like Dataflow (Apache BEAM), DataProc (Apache Spark) and orchestration tools like Apache Airflow is essential.

We are executing a major AI overhaul across our core enterprise data pipelines. Every day, massive volumes of unstructured document images flow through our ingestion engines. We are modernizing this entire supply chain using advanced Document AI, Gemini LLMs, and Agentic workflows to drive straight-through processing.

Key Responsibilities

• Design and implement scalable, high-performance Document Image extraction pipelines using Google Doc AI (including Custom Extractors, Classifiers, and Splitters), ensuring optimal integration, reliability, and incorporating Human-in-the-Loop (HITL) fallback workflows.
  
• Translate business requirements and processes into well-architected technical solutions, aligning with enterprise architecture standards and long-term technology strategy
  
• Define and document solution architecture, technical designs, and requirements to support business objectives while balancing practical implementation and strategic vision
  
• Provide technical leadership and guidance to engineering and support teams, ensuring alignment with business and IT strategies
  
• Develop and present architecture and design artifacts to both technical and non-technical stakeholders
  
• Proactively identify challenges, assess downstream impacts across business domains, and drive solution design through research, validation, and stakeholder consensus
  
• Apply industry and domain best practices, offering architectural guidance and strategic input to business and technology leadership
  
• Evaluate the impact of new solutions on existing architecture, ensuring compliance with enterprise standards and governance frameworks
  
• Contribute to enterprise-wide technology initiatives and support critical issue resolution when needed
  
• Actively participate in team ceremonies, provide status updates, and support overall project governance and execution
  
• Mentor and coach junior engineering team members to foster professional growth.
  

Job Qualifications:

• Bachelor's degree in computer science, Engineering, or a related discipline (or equivalent work experience)
  
• 7+ years of experience in IT, with strong expertise in Gen AI/Agentic AI, Document Image extraction, data architecture, Kubernetes/GKE, and driving continuous improvements-preferably within the mortgage, real estate, finance or insurance domains
  
• Deep understanding of Gen AI/Agentic AI, Machine Learning, Unstructured Data Extraction using hybrid AI/ML, Prompt Engineering, Multi Agent Orcherstration, RAG, Model surveillance/Governance, LLM Token optimization techniques to support strategic architecture planning
  
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  Deep, hands-on expertise with the Google Document AI suite (Form Parser, Custom Document Extractors (CDE), CDE training/tuning) and evaluating extraction model performance (Precision/Recall optimization)
  
  
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  Proven experience designing Human-in-the-Loop (HITL) workflows that are critical for Enterprise Document AI pipelines
  
  
• Strong knowledge of the full lifecycle of Gen AI/ML applications, data engineering pipelines design and development
  
• Proven experience in enterprise application architecture,