luxurypresence - Luxury Presence - Staff Software Engineer, Data Platform
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Requirements
• 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 • 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.) • ◦ 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 provider, with a good grasp of cost, reliability, and security tradeoffs • Experience building or integrating AI agents into production workflows (e.g., internal tools, support automation, operational triage, or data workflows) • Familiarity with frameworks such as PydanticAI, LangGraph, Claude Code or similar, and how they interact with backend services, vector stores, and LLM APIs • Comfort working with logs, telemetry, and evaluation metrics to monitor, debug, and iteratively improve AI-driven systems • Leadership & collaboration • Demonstrated ability to lead technical initiatives across teams, from idea to production (alignment, design, implementation, rollout) • Track record of mentoring other engineers and raising the bar on code quality, testing, and design • Strong communication skills; able to clearly explain complex technical decisions to both engineers and non-technical stakeholders • Customer and product mindset: you care about how the data and services you build improve the end-user and client experience, not just the internals • ◦ Iceberg, Hive, or other table formats/data lake technologies • ◦ Snowflake, Athena, Redshift, or other cloud data warehouses • ◦ dbt or similar transformation frameworks • ◦ Data quality / observability tools (e.g., Great Expectations, Monte Carlo, Datafold) • ◦ Vector databases / retrieval (e.g., LanceDB, Pinecone, Elasticsearch/OpenSearch) • Background in real estate, marketplaces, or other domains where data quality and freshness are highly visible to customers • Prior experience in a startup or high-growth environment where you’ve built or significantly evolved a data platform • The real estate industry is in the midst of a seismic shift, and the future belongs to those who break new ground. As one of the fastest-growing companies in the proptech and marketing sectors, Luxury Presence challenges the status quo of what technology can do for real estate agents, leaders, and brokerages. • We're a team of agile and tenacious innovators working collaboratively to drive the industry forward. Together, we build game-changing products that empower modern real estate entrepreneurs to dominate their markets. From award-winning web design to agile SEO solutions to cutting-edge AI tools, we deliver tech that anticipates market shifts and keeps our clients ahead of their competition. • Founded in 2016 by Stanford Business School alum Malte Kramer, Luxury Presence has grown to a global team ranked on the Inc. 5000 fastest-growing companies list three years in a row. We're backed by world-class investors, including Bessemer Venture Partners, NextEquity Partners, Toba Capital, and Switch Ventures, and have raised $89 million to date. • More than 18,000 real estate businesses rely on our platform, including 30% of the Wall Street Journal RealTrends top agents and teams. Additionally, many of the industry's most powerful brokerages rely on Luxury Presence as a trusted business partner. • Every year since 2020, Luxury Presence has ranked on BuiltIn's Best Place to Work lists. HousingWire named our founder and CEO a 2024 Tech Trendsetter, we've received several Tech100 Awards, and we just scored an Inman Innovation Award for Best AI-Powered Platform.
Responsibilities
• 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
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