Backend Developer

Arpshah Inc. / Doorviser

Role: Backend Developer — Junior, Mid-Level, Senior

Location: Hybrid in Irvine, CA;
Houston, TX;
Austin, TX

Remote Option: Available for select roles on an hourly basis

Benefits: Health benefits for eligible hybrid full-time employees, company equity, dynamic advanced research environment
About Arpshah / Doorviser

Arpshah is building an AI-driven real estate platform designed to transform how people search, analyze, list, and interact with property data. Doorviser is the platform’s Agentic AI layer, powering conversational search, semantic retrieval, intelligent matching, workflow automation, and AI-assisted user interactions across real estate use cases.

Our platform combines structured data, vector databases, multimodal systems, LLM-powered agents, and modern cloud infrastructure to create next-generation real estate technology.
Role Overview

We are seeking Backend Developers from junior to senior level to help build the core infrastructure behind Doorviser and the broader Arpshah platform. This role focuses on scalable APIs, backend architecture, vectorization workflows, multimodal data structures, cloud services, and AI-driven platform development.

You will help develop systems for data ingestion, semantic retrieval, RAG pipelines, LLM integrations, agent workflows, and real-time application infrastructure.
Responsibilities

• Design, build, and maintain scalable backend services and APIs
• Develop data pipelines for structured and unstructured real estate datasets
• Build vectorization and semantic retrieval workflows
• Integrate vector databases such as Pinecone, Weaviate, or similar technologies
• Support RAG pipelines, LLM integrations, and agentic AI services
• Design efficient data models for multimodal AI applications
• Build and maintain cloud-native services across GCP, Firebase, Cloudflare, and Vercel-connected systems
• Improve system performance, scalability, observability, and reliability
• Collaborate with frontend, full-stack, and AI engineers on production delivery
• Contribute to Git Hub-based CI/CD workflows and engineering best practices
• Support rapid experimentation in startup and research-driven environments

Qualifications Junior

• 1+ years of backend development experience, internships, or strong project work
• Familiarity with APIs, databases, and cloud systems
• Exposure to Python, Node.js, Type Script, Go, or similar backend languages
• Strong interest in AI platforms, vector search, and modern cloud systems

Mid-Level

• 3+ years of backend engineering experience
• Experience building scalable APIs and production backend systems
• Familiarity with GCP, Firebase, distributed services, and serverless systems
• Understanding of data pipelines, ETL, and backend architecture
• Familiarity with vector search, embeddings, and LLM integrations

Senior

• 5+ years of backend or platform engineering experience
• Experience architecting large-scale, production-grade backend systems
• Strong understanding of AI application backends, retrieval systems, and multimodal data pipelines
• Ability to lead architecture discussions, mentor engineers, and drive execution

Preferred Qualifications

• M.S. or Ph.D. in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related field
• Preference for candidates from top universities such as UT Austin, MIT, Stanford, UC Berkeley, or equivalent institutions
• Preference for candidates with prior experience at Google, Meta, Microsoft, Amazon, or comparable high-performance technology companies
• Strong familiarity with vectorization, vector databases, multimodal data structures, deep learning, reinforcement learning, RAG, and agentic AI workflows
• Experience building production AI systems in startup or advanced research environments

Employment Type

• Hybrid full-time roles in Irvine, CA;
  Houston, TX;
  Austin, TX
• Remote hourly roles available for select candidates

Benefits

• Health benefits for eligible hybrid full-time roles
• Company equity
• Opportunity to work in a highly dynamic advanced research environment
• Exposure to next-generation AI systems, vector search, multimodal AI, and real-world agentic workflows