Note: The job is a remote job and is open to candidates in USA. Zillow is hiring a Senior Fullstack Engineer to build and operate production-grade agentic AI systems for mortgage fulfillment. The role focuses on agent architecture, evaluation infrastructure, reliable integrations, and the core infrastructure that runs agents.
Responsibilities
- Design and build multi-step AI agents that coordinate Fulfillment workflows such as document collection, condition clearing, and closing coordination, without requiring a person to step in at every step
- Build evaluation frameworks that measure agent reliability, accuracy, and task completion, and use that signal to improve prompts, models, and fallbacks. This is essential for deploying AI safely in a regulated mortgage environment
- Architect and operate core agent infrastructure, including model serving, prompt pipelines, batching, queueing, and observability, designed for reliability: idempotency, retries, graceful degradation, and structured logging
- Build robust integrations with third-party platforms such as Encompass and DocuTech, working within their constraints and extension points to read state and write actions back reliably
- Collaborate closely with Encompass administrators, Fulfillment operations, and Platform engineering partners to refine requirements, break down work, and deliver iteratively
- Set and advocate for engineering best practices in testing, measurement, observability, and incident response, and mentor other engineers through code reviews and design discussions
Skills
- Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or an equivalent combination of education and experience
- 8+ years of professional software engineering experience, including building and operating scalable, reliable services in a modern cloud environment
- Proven experience owning an AI or ML system in production from end to end (designing, shipping, measuring, and iterating on it) with accountability for correctness, cost, and reliability
- Hands-on experience in at least two of these areas: designing and running eval pipelines (including producing labeled data at scale); operating LLM or ML model serving and orchestrating multi-step AI workflows; building reliable integrations with third-party platforms and external APIs
- Strong infrastructure instincts alongside AI fluency
- A bias toward measurement: you define what correct looks like, build the tooling to check it, and use that signal to improve the system
- Comfort with ambiguity and a track record of going deep in a specialized domain
- Or an equivalent combination of education and experience
Benefits
- Eligible for equity awards based on factors such as experience, performance and location.
- Remote position: employees may work from a physical location of their choice in any of the 50 United States, with limited exceptions; the location must be identified to the Company.
- Through Cloud HQ, most employees have the flexibility to work from wherever they’re most productive.
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