Note: The job is a remote job and is open to candidates in USA. LightBox provides data and workflow solutions for commercial real estate and location intelligence. The Senior Software Engineer will build self-service infrastructure and developer-facing tooling to make AI capabilities accessible and reliable, including API gateways, model routing, integration surfaces, observability systems, and knowledge retrieval layers. The role also collaborates with ML engineers and contributes to architecture and technical design decisions.
Responsibilities
- 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
Skills
- 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
- Experience with Model Context Protocol (MCP) or similar structured AI integration standards
- Background in data-intensive platforms, particularly property data, geospatial systems, or document processing pipelines
- Familiarity with model serving frameworks (LiteLLM, OpenRoute, AWS BedRock) and inference optimization
- Experience in real estate technology, financial services, or other regulated/document-heavy industries
- Prior work building observability or evaluation tooling for ML/AI systems
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