Founding AI Platform Engineer
New
Z
ZipdevCommercial real estate AI
United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5 –10 years of professional experience as a software, backend, machine learning, or applied AI engineer.
- Required Skills
- AWSNode.jsTypeScriptRESTful APIs
Requirements
- Have 5–10 years of professional experience as a software, backend, machine learning, or applied AI engineer.
- Have proven experience building and shipping AI-centric systems used by real users in production.
- Bring experience with agentic workflows, LLM pipelines, document extraction, or retrieval systems over unstructured data.
- Have designed and built a platform or major system end to end, making key architectural and technical decisions.
- Have hands-on experience owning production LLM quality, including evaluations, guardrails, and measuring or preventing hallucinations.
- Have strong experience building APIs, backend services, and data pipelines.
- Have experience designing and deploying production systems in cloud environments.
- Be able to work with complex, unstructured data and design reliable extraction, retrieval, and information-management systems.
- Be comfortable handling sensitive enterprise data and balancing accuracy, security, cost, and latency.
- Relevant technologies include Node.js, TypeScript, PostgreSQL, AWS, LLMs, agentic workflows, RAG, document extraction, evaluation frameworks, semantic search, knowledge graphs, data pipelines, multi-tenant systems, and enterprise APIs or third-party connectors.
- Early-stage startup experience, document AI, advanced retrieval, fine-tuning, computer vision, commercial real estate documents or platforms, and forward-deployed engineering are listed as nice-to-haves.
Responsibilities
- Build and own the core AI orchestration platform, from document ingestion and processing to grounded, source-cited answers.
- Design and maintain a multi-provider LLM gateway with prompt caching, record-replay capabilities, and evaluation-gated model routing.
- Develop evaluation frameworks and guardrails to measure LLM output quality, prevent hallucinations, and ensure reliable production performance.
- Build fact-extraction pipelines and semantic matching systems for complex commercial real estate documents, including loan documents and rent rolls.
- Map extracted information to a commercial real estate semantic field dictionary.
- Lead the architecture of a multi-tenant knowledge graph and retrieval layer.
- Implement enterprise governance capabilities, including PII detection, policy checks, human escalation workflows, and cryptographic audit trails.
- Identify reusable functionality across client-specific implementations and incorporate it into the shared platform.
- Design and build reusable integrations with enterprise real estate platforms such as DealCloud and Yardi.
- Collaborate directly with the CEO and forward-deployed engineers to influence product architecture and technical direction.
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