Note: The job is a remote job and is open to candidates in USA. Crexi is reimagining commercial real estate with an AI-powered platform that provides market insights, property marketing, deal management, and auction services. The Senior AI Engineer will build agentic AI systems and multi-step workflows using retrieval, orchestration, tool use, and action layers grounded in proprietary commercial real estate data. The role also focuses on evaluation, monitoring, guardrails, observability, rapid prototyping, and delivering trustworthy AI experiences for real estate professionals.
Responsibilities
- Design and implement multi-step agentic workflows, including routing, planning, tool use, and state management, using frameworks like LangGraph/LangChain to move from user intent to real, completed actions
- Build evaluation frameworks and production monitoring (offline evals, human-in-the-loop annotation) to measure quality, reliability, and business outcomes, not just model metrics
- Build context and retrieval pipelines over Crexi's proprietary CRE data, handling the compound, qualitative queries that structured filters can't answer
- Work primarily with Anthropic frontier models on AWS Bedrock, using Bedrock AgentCore for agent runtime, identity, and memory, and helps evaluate open-weight alternatives on cost, latency, and capability
- Implement guardrails, structured outputs, and graceful ambiguity handling so agentic systems ask for clarification rather than acting on unclear intent, and establishes trace-level observability across LLM calls and tool invocations
- Leverage agentic coding tools (e.g., Claude Code, Codex) for scaffolding, refactoring, test generation, and debugging, while critically reviewing AI-generated output for correctness, security, and performance
- Rapidly prototype against real user feedback, partnering with Product and Design, and helps convert successful prototypes into scalable, reusable capabilities
- Ensure AI outputs are explainable, source-linked, and trustworthy enough to inform real business decisions
Skills
- 5+ years of professional software development experience in production environments with meaningful scope/ownership, including 2+ years hands-on building LLM-powered applications in production
- Real experience with agentic architectures (multi-step pipelines, tool/function calling, state machines, memory), ideally with LangGraph or similar orchestration frameworks
- Strong retrieval design skills: RAG systems, embeddings, vector search, and the judgment to know when retrieval is the problem and when the data is
- Strong Python proficiency and real-world experience building backend services and APIs in production
- Experience with cloud infrastructure (AWS preferred) and modern collaborative workflows (GitHub/GitLab, code reviews, CI/CD)
- Demonstrated use of agentic coding tools (e.g., Claude Code, Codex) in a professional workflow, without compromising quality
- Comfortable operating in ambiguity and fast iteration cycles; experience designing LLM evaluation pipelines (offline evals, production monitoring, human-in-the-loop annotation) is a plus
- Bachelor's degree in Computer Science or related field, or equivalent practical experience
Benefits
- Rapidly growing startup with a dynamic work environment
- Flexible team structure with the ability to progress in career
- Health, Dental, and Vision insurance
- Collaborative culture and numerous team activities
Company Overview
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