Luxury Presence
About the Role
- 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
Who is the Data Platform Squad?
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)
- Deep experience with:
- 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
AI agent experience
- 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
Nice to Have
- Experience with any of:
- 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
Join us in shaping the future of real estate
Originally posted on Himalayas
To apply for this job please visit himalayas.app.
Working in Brazil
Brazil, officially the Federative Republic of Brazil, is the largest country in South America. It is also the world's fifth-largest country by area and the seventh-largest by population, with over 213 million people. Brazil is a federation composed of 26 states and a Federal District, which hosts the capital, Brasília. Its most populous city is São Paulo, followed by Rio de Janeiro. Brazil has the most Portuguese speakers in the world and is the only country in the Americas where Portuguese is an official language.
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