Founding AI Platform Engineer

Zipdev

. Build and own the core AI orchestration platform, from document ingestion and processing to grounded, source-cited answers .

Posted 11/10/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining AI orchestration platforms, focusing on document ingestion, processing, and LLM output quality. Proficient in designing multi-provider LLM gateways and implementing enterprise governance capabilities for sensitive data management.

Highest-signal resume keywords

AI-Centric Systems DevelopmentLLM Pipeline ManagementAPI and Backend Service DevelopmentCloud Environment DeploymentKnowledge Graph Architecture

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Applicant Tracking System Keywords

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Hard Skills

Node.jsTypeScriptPostgreSQLAWSDocument ExtractionEvaluation FrameworksSemantic SearchData PipelinesMulti-Tenant SystemsAgentic Workflows

Tools & Technologies

DealCloudYardi

Industry Keywords

Commercial Real EstateDocument AIKnowledge GraphsForward-Deployed EngineeringSensitive Data Management

Tech Stack

Tools & technologies

AWSCloudJavaScriptNode.jsPostgresTypeScript

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

5–10 years of professional experience as a software, backend, machine learning, or applied AI engineer
Proven experience building and shipping AI-centric systems used by real users in production
Relevant production AI experience including agentic workflows, LLM pipelines, document extraction, or retrieval systems over unstructured data
Demonstrated experience designing and building a platform or major system end to end, making key architectural and technical decisions
Experience with founding or early engineering roles, independently owning a service, leading a 0-to-1 build, or leading a small engineering team
Hands-on experience owning production LLM quality, including evaluation frameworks, guardrails, and measuring and preventing hallucinations or unreliable outputs
Strong experience building APIs, backend services, and data pipelines
Experience designing and deploying production systems in cloud environments
Ability to work with complex, unstructured data and design reliable systems for extraction, retrieval, and information management
Comfortable handling sensitive enterprise data and balancing accuracy, security, cost, and latency
Experience with Node.js and TypeScript
Experience with PostgreSQL
Experience with AWS
Experience with LLMs, agentic workflows, RAG, document extraction, evaluation frameworks, and semantic search
Experience with knowledge graphs, data pipelines, and multi-tenant systems
Experience with enterprise APIs and third-party software connectors
Nice to have: experience at an early-stage startup, ideally seed to Series B, as an early or founding engineer
Nice to have: experience with LLM gateways, document AI, knowledge graphs, or advanced retrieval systems
Nice to have: fine-tuning or computer vision experience
Nice to have: familiarity with financial or commercial real estate documents
Nice to have: experience integrating with DealCloud or Yardi
Nice to have: experience in forward-deployed engineering environments
Based in or near Chicago (nice to have)