Staff Software Engineer, Data Platform - LATAM

About the role

Luxury Presence is building the AI growth platform for real estate. Backed by Bessemer Venture Partners and other top investors, we're a Series C company that has hit $100M in annual recurring revenue. More than 90,000 real estate professionals, including over 30% of the WSJ Real Trends top 100 agents in the United States, use us to run and grow their business. About the Role We're seeking a Staff Software Engineer to strengthen our real estate MLS data platform squad. You will build robust data pipelines and backend services that power: High-quality MLS and property data across 400+ feeds Property discovery and search on agent websites Personalized listing recommendations and other data-driven features Conversational and operational AI agents that streamline internal workflows The evaluation and monitoring infrastructure that keeps these systems improving over time This role sits at the intersection of backend engineering , data infrastructure ,and AI-powered products . Who is the Data Platform Squad? We make sure clean, reliable MLS listing records and user click-stream data are always available to our products and customers. Our current team-a mix of data engineers and software engineers-owns the entire listing pipeline: ingestion, transformation, and normalization across 400+ MLS feeds and other sources. We also extend the platform to capture user-activity data for user-facing features such as personalized listing recommendations, and we build AI agents that automate feed onboarding and listing-issue triage, reducing manual effort for internal teams and clients and shortening the path from data to business impact. What You'll Do Technical leadership & architecture Own the end-to-end architecture for MLS and property data: streaming and batch pipelines , microservices, storage layers, and APIs Design and evolve event-driven , Kafka-based data flows that power listing ingestion, enrichment, recommendations, and AI use cases Drive technical design reviews, set engineering best practices, and make high-quality tradeoffs around reliability, performance, and cost Backend, data & platform engineering Design, build, and operate backend services (Python or Java) that expose listing, property, and recommendation data via robust APIs and microservices Implement scalable data processing with Spark or Flink on EMR (or similar), orchestrated via Airflow and running on Kubernetes where applicable Champion observability (metrics, tracing, logging) and operational excellence (alerting, runbooks, SLOs, on-call participation) for data and backend services Streaming & batch data pipelines Build and maintain high-volume, schema-evolving streaming and batch pipelines that ingest and normalize MLS and third-party data Ensure data quality, lineage, and governance are built into the platform from the start-supporting analytics, AI/ML, and customer-facing features Partner with analytics engineering and data science to make data discoverable and usable (e.g., semantic layers, documentation, self-service tooling) AI agents & data products Collaborate with ML/AI engineers to design and scale AI agents that automate MLS feed onboarding, listing discrepancy triage, and other operational workflows Work with frameworks such as PydanticAI, LangChain, or similar to integrate LLM-based agents into our data and service architecture Help define and implement evaluation, logging, and feedback loops so these agents and data-driven products continuously improve Cross-functional impact & mentorship Collaborate closely with Product, Engineering, and Operations to shape the roadmap for our data platform, MLS capabilities, and AI-powered experiences Translate ambiguous business and customer problems into clear technical strategies and phased delivery plans Mentor and unblock other engineers; elevate the overall level of technical decision-making on the team via pairing, reviews, and design guidance What You'll Bring Experience & scope 10+ years of professional software engineering experience, including owning production systems end-to-end Significant experience working with data-intensive or distributed systems at scale (high volume, high availability) Prior experience in a senior or staff/lead role where you influenced architecture, standards, and technical direction Core technical skills Strong programming skills in Python or Java , with experience building microservices and APIs (REST/GraphQL) Hands-on experience with Apache Kafka or similar event/messaging platforms (Kinesis, Pub/Sub, etc.) Deep experience with: - Spark or Flink for large-scale data processing, across streaming and batch pipelines (on EMR or similar big-data compute) - Airflow (or equivalent orchestration tools) - Kubernetes for running data/compute workloads Strong SQL and data modeling skills; solid understanding of ETL/ELT patterns , data warehousing concepts, and performance tuning Experience building on AWS (preferred) or another major cloud provid

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