• You manage and develop engineers across DevOps, Platform, and AQA. • You will drive the decision process and execution to consolidate these into a coherent, maintainable stack — improving signal quality, reducing tool sprawl, and cutting cost. • You own the AWS infrastructure design for multi-region deployments — networking, data residency, compliance implications, and operational readiness. • Your Platform team works directly with stream-aligned teams to identify and resolve systemic performance risks — including query tagging, timeout analysis, and database-level bottlenecks that can cascade into incidents. • You own our CircleCI pipelines — speed, reliability, and cost. • Your AQA team owns automated testing across the organisation — Playwright-based end-to-end tests, test suite maintenance, and the quality gate that governs every release. • You work with your Platform team to improve the internal tooling that stream-aligned engineers depend on daily.

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.

• Lead multiple Mason pods and own delivery outcomes • Translate ambiguous requests into clear plans and execution strategy • Set and enforce production-quality standards for Mason builds • Serve as technical escalation for difficult problems • Establish and evolve team processes • Drive prioritization and capacity planning across pods • Partner with Delivery Leads and stakeholders • Hire and build the team • Manage performance and develop leaders within the Mason org