Senior Software Engineer, Applied AI Services

Zillow Zillow · Consumer · Mexico City, Mexico

Senior Software Engineer role focused on building and scaling end-to-end intelligent systems that power personalized experiences and Home Details Page (HDP) capabilities. The role involves working with scalable backend services and applied AI/ML systems, including data pipelines, LLM/ML-powered capabilities, evaluation frameworks, and AI-driven workflows. Responsibilities include designing, building, and maintaining data pipelines, developing and integrating ML/LLM capabilities, designing prompts and evaluation systems, and translating prototypes into production-hardened systems. The role operates at the intersection of backend services and applied AI/ML, aiming to turn user intent into intelligence and scale AI capabilities across the shopper journey.

What you'd actually do

  1. Lead end-to-end delivery of features — from early prototypes to production-hardened systems.
  2. Work deeply with AI/ML workflows while applying solid engineering and reliability practices.
  3. Design, build, and maintain data pipelines (e.g., Spark, Databricks, Python, Kafka or equivalents) that turn raw events and signals into durable features and model inputs.
  4. Develop and integrate ML/LLM capabilities (e.g., embeddings, similarity search, ranking, clustering, text generation) into backend flows and expose them via stable, well-versioned services and APIs for product teams to consume.
  5. Design and iterate on prompts, configurations, and AI workflows using notebooks and offline experimentation, and build automated evaluation systems (e.g., LLM-as-judge, regression suites, sampling pipelines) with clear quality metrics for accuracy, safety, latency, and cost.

Skills

Required

  • Strong proficiency in at least one backend programming language (Python, Java, Kotlin, or similar)
  • Delivered scalable services or APIs to production in a cloud environment (AWS, GCP)
  • Hands-on experience with data processing or distributed systems (Spark, Databricks, Kafka or similar data pipelines)
  • Familiarity with designing and consuming APIs (REST or GraphQL)
  • Shipped at least one ML or LLM-based feature or capability to production
  • Familiarity with embeddings, ranking, clustering, recommendations, or other ML applications
  • Experience with prompt engineering and LLM-based product development
  • Experience with safety/guardrail considerations for AI features
  • Experience with offline/online evaluation frameworks for AI-powered features
  • Comfortable in modern infrastructure environments (Kubernetes-based deployments, event-driven architectures, observability stacks)
  • Track record of owning projects end-to-end

Nice to have

  • Experience with AI/ML workflows
  • Experience with AI/ML and Agentic AI teams
  • Experience with RAG
  • Experience with vector databases
  • Experience with model serving

What the JD emphasized

  • build and scale end-to-end intelligent systems
  • applied AI/ML systems
  • LLM/ML-powered capabilities
  • AI-driven workflows
  • bring 0->1 AI capabilities
  • scale them across Zillow’s shopper journey surfaces
  • integrate ML/LLM capabilities
  • automated evaluation systems
  • bring 0->1 AI capabilities to customers and evolve them to 1->N

Other signals

  • building and scaling end-to-end intelligent systems
  • applied AI/ML systems
  • LLM/ML-powered capabilities
  • AI-driven workflows
  • bring 0->1 AI capabilities
  • scale them across Zillow’s shopper journey surfaces
  • integrate ML/LLM capabilities
  • automated evaluation systems
  • bring 0->1 AI capabilities to customers and evolve them to 1->N