Tacit Analytics Ltd.
About Tacit We're hiring engineers who want to work at the intersection of AI and the built environment and help make the world's buildings dramatically smarter. Tacit is a University College London (UCL) spinout turning over a decade of research into commercial reality. We extract fragmented building data (BMS feeds, BIM models, IoT sensors, maintenance logs) and integrate it into a contextual layer that enables explainable AI agents to diagnose, decide, and act. We're early-stage, well-funded, and already deploying with real clients across heritage, education, and commercial portfolios. Here's what you'll be doing This is a product engineering role: you'll own the full stack, from how building data flows in to how it's stored, queried, and surfaced to users and AI agents. You'll make real architectural decisions and work directly with the founders. Design and build the core data ingestion and retrieval systems that handle BMS telemetry, BIM models, IoT streams, and metadata, using Python, Java, Go (Django, Spring, EdgeX frameworks). Build the features clients interact with daily across React, TypeScript, and our backend. Own the knowledge graph infrastructure (RDF triple stores such as GraphDB or Fuseki, SPARQL endpoints, SHACL validation) and ensure it performs at portfolio scale. Build and expose the Universal Building API (GraphQL/REST) that powers our 3D twin, AI agents, and third-party integrations. You need these qualifications You have 4+ years of software engineering experience. You've built and operated systems in production: APIs, databases, task queues, caching, deployments. Proficient in Python or Java (Django or Spring), PostgreSQL, GraphQL. Comfortable with full-stack development with React, TypeScript, TanStack, Tailwind. You've designed and operated data-intensive systems and understand architectural concepts like schema design, migrations, query performance, indexing, caching. Experience with containerisation and deployment tooling such as Docker, Kubernetes, and Terraform. Ability to operate with high autonomy in an early-stage environment. You are comfortable making decisions with incomplete information and owning the outcomes. It would be nice if You've worked with knowledge graphs, RDF, SPARQL, or graph databases (Neo4j, Ontotext GraphDB, Fuseki). You've built APIs with GraphQL (Strawberry, Ariadne, or similar) and/or worked with semantic web technologies (OWL, SHACL). You have experience with actor-based concurrency frameworks (Apache Pekko, Akka) or event-driven architectures. You've worked in the built environment, PropTech, or industrial IoT. What we offer Competitive salary (adjusted by location) plus equity in the business. Pension contribution. Flexible, remote-first working. We get together in London and Athens regularly, so expect around 10-20% travel. Dedicated AI-focused learning and development budget.
About Tacit We're hiring engineers who want to work at the intersection of AI and the built environment and help make the world's buildings dramatically smarter. Tacit is a University College London (UCL) spinout turning over a decade of research into commercial reality. We extract fragmented building data (BMS feeds, BIM models, IoT sensors, maintenance logs) and integrate it into a contextual layer that enables explainable AI agents to diagnose, decide, and act. We're early-stage, well-funded, and already deploying with real clients across heritage, education, and commercial portfolios. Here's what you'll be doing This is a product engineering role: you'll own the full stack, from how building data flows in to how it's stored, queried, and surfaced to users and AI agents. You'll make real architectural decisions and work directly with the founders. Design and build the core data ingestion and retrieval systems that handle BMS telemetry, BIM models, IoT streams, and metadata, using Python, Java, Go (Django, Spring, EdgeX frameworks). Build the features clients interact with daily across React, TypeScript, and our backend. Own the knowledge graph infrastructure (RDF triple stores such as GraphDB or Fuseki, SPARQL endpoints, SHACL validation) and ensure it performs at portfolio scale. Build and expose the Universal Building API (GraphQL/REST) that powers our 3D twin, AI agents, and third-party integrations. You need these qualifications You have 4+ years of software engineering experience. You've built and operated systems in production: APIs, databases, task queues, caching, deployments. Proficient in Python or Java (Django or Spring), PostgreSQL, GraphQL. Comfortable with full-stack development with React, TypeScript, TanStack, Tailwind. You've designed and operated data-intensive systems and understand architectural concepts like schema design, migrations, query performance, indexing, caching. Experience with containerisation and deployment tooling such as Docker, Kubernetes, and Terraform. Ability to operate with high autonomy in an early-stage environment. You are comfortable making decisions with incomplete information and owning the outcomes. It would be nice if You've worked with knowledge graphs, RDF, SPARQL, or graph databases (Neo4j, Ontotext GraphDB, Fuseki). You've built APIs with GraphQL (Strawberry, Ariadne, or similar) and/or worked with semantic web technologies (OWL, SHACL). You have experience with actor-based concurrency frameworks (Apache Pekko, Akka) or event-driven architectures. You've worked in the built environment, PropTech, or industrial IoT. What we offer Competitive salary (adjusted by location) plus equity in the business. Pension contribution. Flexible, remote-first working. We get together in London and Athens regularly, so expect around 10-20% travel. Dedicated AI-focused learning and development budget.
Tacit Analytics Ltd.
About Tacit We're hiring engineers who want to work at the intersection of AI and the built environment and help make the world's buildings dramatically smarter. Tacit is a University College London (UCL) spinout turning over a decade of research into commercial reality. We extract fragmented building data (BMS feeds, BIM models, IoT sensors, maintenance logs) and integrate it into a contextual layer that enables explainable AI agents to diagnose, decide, and act. We're early-stage, well-funded, and already deploying with real clients across heritage, education, and commercial portfolios. Here's what you'll be doing This is a product engineering role: you'll own the full stack, from how building data flows in to how it's stored, queried, and surfaced to users and AI agents. You'll make real architectural decisions and work directly with the founders. Design and build the core data ingestion and retrieval systems that handle BMS telemetry, BIM models, IoT streams, and metadata, using Python, Java, Go (Django, Spring, EdgeX frameworks). Build the features clients interact with daily across React, TypeScript, and our backend. Own the knowledge graph infrastructure (RDF triple stores such as GraphDB or Fuseki, SPARQL endpoints, SHACL validation) and ensure it performs at portfolio scale. Build and expose the Universal Building API (GraphQL/REST) that powers our 3D twin, AI agents, and third-party integrations. You need these qualifications You have 4+ years of software engineering experience. You've built and operated systems in production: APIs, databases, task queues, caching, deployments. Proficient in Python or Java (Django or Spring), PostgreSQL, GraphQL. Comfortable with full-stack development with React, TypeScript, TanStack, Tailwind. You've designed and operated data-intensive systems and understand architectural concepts like schema design, migrations, query performance, indexing, caching. Experience with containerisation and deployment tooling such as Docker, Kubernetes, and Terraform. Ability to operate with high autonomy in an early-stage environment. You are comfortable making decisions with incomplete information and owning the outcomes. It would be nice if You've worked with knowledge graphs, RDF, SPARQL, or graph databases (Neo4j, Ontotext GraphDB, Fuseki). You've built APIs with GraphQL (Strawberry, Ariadne, or similar) and/or worked with semantic web technologies (OWL, SHACL). You have experience with actor-based concurrency frameworks (Apache Pekko, Akka) or event-driven architectures. You've worked in the built environment, PropTech, or industrial IoT. What we offer Competitive salary (adjusted by location) plus equity in the business. Pension contribution. Flexible, remote-first working. We get together in London and Athens regularly, so expect around 10-20% travel. Dedicated AI-focused learning and development budget.
About Tacit We're hiring engineers who want to work at the intersection of AI and the built environment and help make the world's buildings dramatically smarter. Tacit is a University College London (UCL) spinout turning over a decade of research into commercial reality. We extract fragmented building data (BMS feeds, BIM models, IoT sensors, maintenance logs) and integrate it into a contextual layer that enables explainable AI agents to diagnose, decide, and act. We're early-stage, well-funded, and already deploying with real clients across heritage, education, and commercial portfolios. Here's what you'll be doing This is a product engineering role: you'll own the full stack, from how building data flows in to how it's stored, queried, and surfaced to users and AI agents. You'll make real architectural decisions and work directly with the founders. Design and build the core data ingestion and retrieval systems that handle BMS telemetry, BIM models, IoT streams, and metadata, using Python, Java, Go (Django, Spring, EdgeX frameworks). Build the features clients interact with daily across React, TypeScript, and our backend. Own the knowledge graph infrastructure (RDF triple stores such as GraphDB or Fuseki, SPARQL endpoints, SHACL validation) and ensure it performs at portfolio scale. Build and expose the Universal Building API (GraphQL/REST) that powers our 3D twin, AI agents, and third-party integrations. You need these qualifications You have 4+ years of software engineering experience. You've built and operated systems in production: APIs, databases, task queues, caching, deployments. Proficient in Python or Java (Django or Spring), PostgreSQL, GraphQL. Comfortable with full-stack development with React, TypeScript, TanStack, Tailwind. You've designed and operated data-intensive systems and understand architectural concepts like schema design, migrations, query performance, indexing, caching. Experience with containerisation and deployment tooling such as Docker, Kubernetes, and Terraform. Ability to operate with high autonomy in an early-stage environment. You are comfortable making decisions with incomplete information and owning the outcomes. It would be nice if You've worked with knowledge graphs, RDF, SPARQL, or graph databases (Neo4j, Ontotext GraphDB, Fuseki). You've built APIs with GraphQL (Strawberry, Ariadne, or similar) and/or worked with semantic web technologies (OWL, SHACL). You have experience with actor-based concurrency frameworks (Apache Pekko, Akka) or event-driven architectures. You've worked in the built environment, PropTech, or industrial IoT. What we offer Competitive salary (adjusted by location) plus equity in the business. Pension contribution. Flexible, remote-first working. We get together in London and Athens regularly, so expect around 10-20% travel. Dedicated AI-focused learning and development budget.