LightBox

• Drive new enterprise data bookings through direct sales into capital markets institutions. • Structure and negotiate complex data licensing agreements (national, regional, API, Snowflake, bulk feeds). • Engage with CIOs, Heads of Data, Portfolio Managers, Risk Teams, and Investment Committees. • Position LightBox as the identity backbone for institutional property and participant intelligence. • Navigate procurement, legal, and data governance review processes. • Collaborate cross-functionally with Product, Legal, Revenue Operations, and Customer Success. • Develop territory strategies and named account plans. • Identify upsell opportunities tied to ownership intelligence, transaction history, hazard overlays, infrastructure context, and derived insights. • Build multi-threaded relationships within large enterprise accounts.

• 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.

• Build, enhance, and maintain modern web applications for LightBox Live. • Develop responsive, intuitive, and performant user interfaces using React and TypeScript. • Collaborate with product, design, and engineering teammates to translate business needs and user workflows into high quality software. • Use AI-assisted development tools thoughtfully to accelerate implementation, testing, refactoring, debugging, documentation, and technical exploration while maintaining strong ownership of code quality and correctness. • Work with APIs, data models, and backend services in a Node-based application environment. • Participate in architecture discussions, technical design reviews, pull requests, and code reviews. • Help shape reusable components, patterns, and best practices across the application. • Analyze, troubleshoot, and resolve technical and application issues. • Write clean, maintainable, well tested code. • Contribute to an agile development process focused on delivering meaningful product value.

• Research and resolve exceptions identified through automated data quality, validation, and exception management processes. • Analyze location-related records using GIS tools, aerial imagery, parcel data, address datasets, building footprints, geocodes, and other authoritative sources. • Execute SQL queries to investigate data anomalies, compare records across datasets, validate data accuracy, and support exception resolution. • Apply established business rules, procedures, and quality standards to determine appropriate resolutions for flagged records. • Document research findings, decisions, and supporting information in accordance with internal quality, audit, and process documentation standards. • Maintain productivity and quality standards while processing a structured queue of exception-based research tasks. • Identify trends, recurring exception patterns, root causes, and data quality issues and provide feedback to improve processes, automation, and data integrity. • Collaborate with data operations, GIS, product, and related teams to support data quality, process improvement, and operational efficiency. • Assist in the development, refinement, and maintenance of research procedures, quality controls, standard operating procedures, and training documentation. • Use GIS platforms and related tools to review spatial relationships, validate location accuracy, interpret imagery, and assess property-related records. • Support continuous improvement efforts that increase the accuracy, consistency, efficiency, and scalability of geospatial data quality processes.

• Drive new enterprise data bookings through direct sales into capital markets institutions. • Structure and negotiate complex data licensing agreements (national, regional, API, Snowflake, bulk feeds). • Engage with CIOs, Heads of Data, Portfolio Managers, Risk Teams, and Investment Committees. • Position LightBox as the identity backbone for institutional property and participant intelligence. • Navigate procurement, legal, and data governance review processes. • Collaborate cross-functionally with Product, Legal, Revenue Operations, and Customer Success. • Develop territory strategies and named account plans. • Identify upsell opportunities tied to ownership intelligence, transaction history, hazard overlays, infrastructure context, and derived insights. • Build multi-threaded relationships within large enterprise accounts.

• 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.

• Build, enhance, and maintain modern web applications for LightBox Live. • Develop responsive, intuitive, and performant user interfaces using React and TypeScript. • Collaborate with product, design, and engineering teammates to translate business needs and user workflows into high quality software. • Use AI-assisted development tools thoughtfully to accelerate implementation, testing, refactoring, debugging, documentation, and technical exploration while maintaining strong ownership of code quality and correctness. • Work with APIs, data models, and backend services in a Node-based application environment. • Participate in architecture discussions, technical design reviews, pull requests, and code reviews. • Help shape reusable components, patterns, and best practices across the application. • Analyze, troubleshoot, and resolve technical and application issues. • Write clean, maintainable, well tested code. • Contribute to an agile development process focused on delivering meaningful product value. • Help modernize and unify CRE workflows by making complex data easier to understand and act on.

• Research and resolve exceptions identified through automated data quality, validation, and exception management processes. • Analyze location-related records using GIS tools, aerial imagery, parcel data, address datasets, building footprints, geocodes, and other authoritative sources. • Execute SQL queries to investigate data anomalies, compare records across datasets, validate data accuracy, and support exception resolution. • Apply established business rules, procedures, and quality standards to determine appropriate resolutions for flagged records. • Document research findings, decisions, and supporting information in accordance with internal quality, audit, and process documentation standards. • Maintain productivity and quality standards while processing a structured queue of exception-based research tasks. • Identify trends, recurring exception patterns, root causes, and data quality issues and provide feedback to improve processes, automation, and data integrity. • Collaborate with data operations, GIS, product, and related teams to support data quality, process improvement, and operational efficiency. • Assist in the development, refinement, and maintenance of research procedures, quality controls, standard operating procedures, and training documentation. • Use GIS platforms and related tools to review spatial relationships, validate location accuracy, interpret imagery, and assess property-related records. • Support continuous improvement efforts that increase the accuracy, consistency, efficiency, and scalability of geospatial data quality processes.

At LightBox, we strive to not only equip confident, data-driven decisions across sectors, but to also enrich lives by bringing people, information, and technology together. As a company with a wide range of clients, we believe a diverse workforce is crucial to success. Our commitment to inclusion across race, gender, age, religion, identity, and experience is the foundation upon which we operate and connect with our customers and the communities in which we work. With our expertise, we are producing the best available data, workflow tools, technology, and analytics to support everyone making a real estate decision. There has never been a better time to make an impact and we invite you to join us on this journey. LightBox is a leading provider of data and workflow solutions across commercial real estate and location intelligence. Our solutions deliver the depth, speed and accuracy that enable insights to over 50,000 brokers, 1,000 banks and lenders, 1,000 law firms and 5,000 environmental consulting and engineering firms. The Role As Senior Engineer - AI Platform, you will build the self-service infrastructure and developer-facing tooling that makes LightBox's AI capabilities accessible and reliable. You'll work across the stack - from MCP server implementations and API gateways to internal developer tools and integration surfaces - ensuring that AI models and agents can be composed, deployed, and consumed by both internal teams and external partners. This role sits at the intersection of platform engineering and applied AI. You won't just be writing CRUD endpoints; you'll be building the connective tissue between proprietary CRE data, specialized AI models, and the production applications that hundreds of thousands of industry professionals use daily. What You'll Do - 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. What We're Looking For Required - 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. Preferred - 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. We thank all applicants in advance for their interest in this position, however, only those selected for an interview will be contacted. This job description is a general listing of the required tasks and expectations of the position and in no way implies that the duties listed above are the employee’s only responsibilities. The employee is expected to perform other tasks, responsibilities and training as instructed by their supervisors. Duties and responsibilities may change at any time with or without notice. This position may require additional hours outside of the standard work schedule including occasional holiday, evening and/or weekend hours in order to meet deadlines or to accommodate customers. LightBox and all its holding companies are an equal opportunity/affirmative action employer. It is the policy of the LightBox and its holding companies to prohibit discrimination of any type and to afford equal employment opportunities to employees and applicants, without regard to race, color, religion, sex, national origin, age, disability, or veteran status. NO TELEPHONE CALLS OR AGENCY SOLICITATION PLEASE.

At LightBox, we strive to not only equip confident, data-driven decisions across sectors, but to also enrich lives by bringing people, information, and technology together. As a company with a wide range of clients, we believe a diverse workforce is crucial to success. Our commitment to inclusion across race, gender, age, religion, identity, and experience is the foundation upon which we operate and connect with our customers and the communities in which we work. With our expertise, we are producing the best available data, workflow tools, technology, and analytics to support everyone making a real estate decision. There has never been a better time to make an impact and we invite you to join us on this journey. LightBox is a leading provider of data and workflow solutions across commercial real estate and location intelligence. Our solutions deliver the depth, speed and accuracy that enable insights to over 50,000 brokers, 1,000 banks and lenders, 1,000 law firms and 5,000 environmental consulting and engineering firms. The Role As Senior Engineer - AI Platform, you will build the self-service infrastructure and developer-facing tooling that makes LightBox's AI capabilities accessible and reliable. You'll work across the stack - from MCP server implementations and API gateways to internal developer tools and integration surfaces - ensuring that AI models and agents can be composed, deployed, and consumed by both internal teams and external partners. This role sits at the intersection of platform engineering and applied AI. You won't just be writing CRUD endpoints; you'll be building the connective tissue between proprietary CRE data, specialized AI models, and the production applications that hundreds of thousands of industry professionals use daily. What You'll Do - 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. What We're Looking For Required - 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. Preferred - 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. We thank all applicants in advance for their interest in this position, however, only those selected for an interview will be contacted. This job description is a general listing of the required tasks and expectations of the position and in no way implies that the duties listed above are the employee’s only responsibilities. The employee is expected to perform other tasks, responsibilities and training as instructed by their supervisors. Duties and responsibilities may change at any time with or without notice. This position may require additional hours outside of the standard work schedule including occasional holiday, evening and/or weekend hours in order to meet deadlines or to accommodate customers. LightBox and all its holding companies are an equal opportunity/affirmative action employer. It is the policy of the LightBox and its holding companies to prohibit discrimination of any type and to afford equal employment opportunities to employees and applicants, without regard to race, color, religion, sex, national origin, age, disability, or veteran status. NO TELEPHONE CALLS OR AGENCY SOLICITATION PLEASE.