Principal, AI Engineering
$134,400–$185,000 year
On-siteDallas, Texas, United States or Irvine, California, United States
Dallas, Texas, United States or Irvine, California, United StatesOn-siteFull Time$134,400–$185,000 yearSenior LevelLarge
Full TimeSenior LevelLarge
Job Summary
Design and implement scalable Document Image extraction pipelines using Google Doc AI, Custom Extractors, and Splitters to modernize core enterprise data pipelines. Translate business requirements into well-architected technical solutions involving Gen AI, Agentic workflows, and Human-in-the-Loop fallbacks. Define solution architecture and design artifacts for stakeholders while providing technical leadership to engineering teams. Mentor junior members, drive research and validation, and ensure compliance with enterprise governance standards.
Required 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
- 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)
- 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, including governance, standards, and strategy development
- Demonstrated ability to resolve complex enterprise-wide application & data architecture challenges
- Expertise in designing solutions aligned with strategic technology roadmaps and emerging industry trends
- Proficiency with data modeling tools and strong experience across SQL and NoSQL technologies
- Hands-on experience with Google Document AI, Prompt Engineering, and AI-native development frameworks or lifecycle methodologies (e.g., BMAD, Spec Kit)
- Deep GCP expertise
- strong hands-on skills in Python, PySpark, and modern graph databases (e.g., Neo4j)
- Proven experience building pipelines using distributed processing (Spark, Hadoop, Elasticsearch) and orchestration platforms (Google Cloud Dataflow, Apache Beam, Apache Airflow)
- Ability to translate complex requirements into detailed technical designs, specifications, and enterprise system architecture
- Proven ability to guide engineering teams, drive architectural best practices, and elevate code quality through active mentorship, reviews, and collaborative pairing
- Strong communication skills with the ability to bridge business requirements, challenge vendor approaches, and align technical strategy with executive stakeholders
- Ability to navigate complex, multi-phase delivery roadmaps and balance competing priorities in a dynamic environment
Desired Qualifications
- AWS or Azure experience (to complement GCP)
- Real Estate, Mortgage, Finance, or Insurance domain knowledge
- Modern graph databases (e.g., Neo4j)
- Event-driven architecture or streaming frameworks (e.g., Kafka)
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.