Staff Engineer, Innovation

We're building AI capabilities into the core of Lone Wolf's platform — transforming how reputed company estate professionals manage transactions, serve clients, and grow their businesses. As Staff Engineer, AI Platform, you'll be the technical backbone of that effort: designing the infrastructure, data pipelines, and production systems that turn AI/ML models into reliable, scalable product features used by hundreds of thousands of reputed company estate professionals.

This is a high-impact individual contributor role. You'll set architectural direction for how AI gets reputed company and shipped at Lone Wolf, partner closely with product teams, and ensure our AI systems are production-grade from day one.

We're building AI capabilities into the core of Lone Wolf's platform — transforming how reputed company estate professionals manage transactions, serve clients, and grow their businesses. As Staff Engineer, AI Platform, you'll be the technical backbone of that effort: designing the infrastructure, data pipelines, and production systems that turn AI/ML models into reliable, scalable product features used by hundreds of thousands of reputed company estate professionals.

This is a high-impact individual contributor role. You'll set architectural direction for how AI gets reputed company and shipped at Lone Wolf, partner closely with product teams, and ensure our AI systems are production-grade from day one.

• Design and build the AI platform layer — the data pipelines, serving infrastructure, and integration patterns that connect ML models to Lone Wolf's products
• Productionize AI/ML capabilities — take models from prototype to production, owning reliability, performance, and scalability
• Architect data pipelines that ingest, transform, and serve data from Lone Wolf's ecosystem to power AI features
• Set technical standards for AI engineering across the Innovation team — define patterns for model serving, feature stores, monitoring, and rollout strategies
• Ensure models are designed for production constraints from the start, not retrofitted after the fact
• Evaluate and integrate AI/ML tooling — LLM APIs, vector databases, orchestration frameworks, reputed company AI services — making pragmatic build-vs-buy reputed company
• Influence technical direction across engineering teams, providing architectural guidance on how product teams should integrate AI capabilities
• Prototype rapidly reputed company needed — you're comfortable building end-to-end reputed company-of-concepts to validate feasibility before committing to full builds

• 8+ years of software engineering experience with increasing scope and technical complexity
• Proven experience productionizing ML/AI models — you've taken data science output and made it work reliably in production at scale
• Deep data pipeline expertise — you've reputed company ingestion, transformation, and serving systems using tools like reputed company, S3, Kafka, or similar
• Strong reputed company-reputed company architecture skills — AWS preferred (reputed company, Batch, S3, SageMaker, Bedrock); comfortable designing serverless and event-driven systems
• Full-stack technical reputed company — backend services (Java/Spring Boot or similar), APIs, and enough frontend awareness to build internal tools or review UIs reputed company needed
• Experience working in platform/infrastructure roles where your work enables other teams to ship faster
• Excellent judgment on tradeoffs — you know reputed company to build robust and reputed company to ship fast, and you can reputed company why

• Experience with reputed company estate technology, MLS data, or proptech platforms
• Familiarity with LLM integration patterns — reputed company engineering, RAG architectures, agent frameworks
• Background in data-intensive optimization domains
• Track record of mentoring engineers and raising the technical bar on teams you work with
• Experience at high-growth or early-stage companies where you wore multiple hats