Luxury Presence is hiring a Staff Software Engineer to join our Data Platform Squad. You will be a key technical leader building robust data pipelines and backend services that power high-quality MLS and property data across 400+ feeds. This role sits at the intersection of backend engineering, data infrastructure, and AI-powered products.
What You'll Do
- Own the end-to-end architecture for MLS and property data, including 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.
- Design, build, and operate backend services in 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 and operational excellence for data and backend services, including alerting, runbooks, SLOs, and on-call participation.
- 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 to support analytics, AI/ML, and customer-facing features.
- Partner with analytics engineering and data science to make data discoverable and usable through semantic layers, documentation, and self-service tooling.
- 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 AI-driven products continuously improve.
- 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 to elevate the overall level of technical decision-making on the team.
What We're Looking For
- 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.
- 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.
- Hands-on experience with Apache Kafka or similar event/messaging platforms.
- Deep experience with Spark or Flink for large-scale data processing across streaming and batch pipelines.
- Deep experience with Airflow or equivalent orchestration tools.
- Deep experience with Kubernetes for running data/compute workloads.
- Strong SQL and data modeling skills and a solid understanding of ETL/ELT patterns and data warehousing concepts.
- Experience building on AWS or another major cloud provider, with a good grasp of cost, reliability, and security tradeoffs.
- Experience building or integrating AI agents into production workflows.
- Familiarity with frameworks such as PydanticAI, LangGraph, or similar and how they interact with backend services and LLM APIs.
- Comfort working with logs, telemetry, and evaluation metrics to monitor, debug, and iteratively improve AI-driven systems.
- Demonstrated ability to lead technical initiatives across teams, from idea to production.
- Track record of mentoring other engineers and raising the bar on code quality, testing, and design.
- Strong communication skills and the ability to clearly explain complex technical decisions to both engineers and non-technical stakeholders.
- Customer and product mindset focused on how your work improves the end-user and client experience.
Nice to Have
- Experience with Iceberg, Hive, or other table formats/data lake technologies.
- Experience with Snowflake, Athena, Redshift, or other cloud data warehouses.
- Experience with dbt or similar transformation frameworks.
- Experience with data quality or observability tools like Great Expectations or Monte Carlo.
- Experience with vector databases or retrieval systems like LanceDB or Pinecone.
- 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.
Technical Stack
- Languages: Python, Java
- Data Streaming/Messaging: Apache Kafka
- Data Processing: Spark, Flink, EMR
- Orchestration: Airflow
- Infrastructure: Kubernetes, AWS
- Databases: SQL
- AI/ML Frameworks: PydanticAI, LangChain
- API Styles: GraphQL, REST
Team & Environment
You'll join the Data Platform Squad, which is a mix of data engineers and software engineers.
Work Mode
This is a remote position for candidates based anywhere in Canada.
