> Markdown version of [/jobs/ext/2654144-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2654144-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Commercial Real Estate Exchange, Inc. - **Location:** Los Angeles, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $179,000.0 - $241,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Code Review, Continuous Integration, Software Debugging, Github, Python (Programming Language), Search Technologies, Software Engineering, Large Language Models, State Machines, Backend, Gitlab, Kubernetes, Information Technology, Code Restructuring - **Published:** August 11, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=691f10baa282132a ## About the Role * 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. Who You Are: * Thrives in a fast-paced, dynamic environment. * Exceptional communication skills, with the ability to provide clear and concise information to stakeholders at all levels of the organization. * Strong analytical skills, with the ability to interpret complex information, identify patterns, and present insights clearly and accurately. * Excellent organizational and prioritization skills, with the ability to manage multiple priorities and deadlines simultaneously. * Self-starter who independently owns their own success and demonstrates strong initiative. * Responsive, action-oriented, and proactive in identifying and resolving issues. * Strong problem-solving and creative thinking skills, with the ability to evaluate options and implement effective solutions. * Effective collaborator and team player, with the ability to work cross-functionally and build strong working relationships. * Demonstrated ability to handle sensitive and confidential information with the utmost professionalism and discretion. ## Description The AI Engineer builds the agentic AI systems that power Crexi's platform, including orchestration, retrieval, and action layers grounded in Crexi's proprietary commercial real estate data. The role builds multi-step agentic workflows that understand user intent, orchestrate the right capabilities, and complete real work, not just answer questions, using tools like LangGraph and AWS Bedrock AgentCore. It exists to extend Crexi's AI-powered research, document generation, and zoning intelligence into unified, trustworthy agentic experiences for brokers, appraisers, lenders, and investors. What You'll Do: A typical day may include: * 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. ## Related Videos - [WeAreDevelopers LIVE - Modern DevOps for IoT Devices and More](https://www.wearedevelopers.com/videos/1805-wearedevelopers-live-modern-devops-for-iot-devices-and-more) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Enabling automated 1-click customer deployments with built-in quality and security](https://www.wearedevelopers.com/videos/83-enabling-automated-1-click-customer-deployments-with-built-in-quality-and-security) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [13 AI Tools You Have to Try](https://www.wearedevelopers.com/magazine/219-13-ai-tools-you-have-to-try) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care)