Senior Software Engineer – Data Platform

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LightBox

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2019

🏠 Real Estate

☁️ SaaS

🤝 B2B

Real Estate • SaaS • B2B

LightBox is a provider of connected property data, location intelligence, and workflow software for commercial real estate professionals. The company aggregates authoritative parcel, ownership, zoning, transaction, building footprint, geocoding, environmental and valuation datasets and exposes them through products such as LightBox Vision (formerly LandVision), APIs, bulk data delivery, valuation and marketing tools, and professional services. LightBox positions itself as a B2B SaaS platform that helps customers locate, analyze, and act on commercial real estate information for use cases including capital markets, environmental due diligence, lending, valuation, and government/utility workflows.

📋 Description

• Design and implement API gateways, model routing layers, and service infrastructure that connect fine-tuned CRE models with production applications. • Develop internal developer tooling - prompt management interfaces, evaluation dashboards, trace viewers - that accelerate the team's ability to ship and iterate on AI features. • Implement integration patterns for embedding AI capabilities into LightBox's existing workflow applications, ensuring seamless user experiences. • Build observability and monitoring infrastructure for AI workloads: latency tracking, quality metrics, cost attribution, and usage analytics. • Contribute to the platform's knowledge retrieval and caching layers, optimizing for both accuracy and performance at scale. • Collaborate with ML engineers on model serving infrastructure, helping bridge the gap between training outputs and production deployment. • Participate in architecture decisions and technical design reviews, bringing a pragmatic full-stack perspective to the team's work.

🎯 Requirements

• 6+ years of software engineering experience with a strong full-stack foundation (backend-leaning preferred). • Production experience building APIs, microservices, and platform infrastructure in Python and/or TypeScript/Node.js. • Solid understanding of cloud infrastructure (AWS or GCP), containerization (Docker, Kubernetes), and CI/CD pipelines. • Experience building developer-facing tools, SDKs, or internal platforms that other engineers consume. • Familiarity with LLM integration patterns: API-based model consumption, prompt engineering, retrieval-augmented generation, and tool/function calling. • Strong fundamentals in distributed systems, data modeling, and API design. • Comfort working in a small team with high autonomy - you can own a feature end-to-end from design through deployment and monitoring.