Predictive & Agentic AI Engineer

Are you an accomplished AI practitioner with a passion for developing cutting-edge analytics, predictive machine learning, and multi-agent generative AI solutions? If you have at least five years of hands-on experience in data science, combined with proven capabilities in building autonomous agentic workflows within the AWS ecosystem and Enterprise Agent Platforms, we have an exciting opportunity for you!

As a Predictive & Agentic AI Engineer , you will bridge the gap between traditional predictive modeling and state-of-the-art generative AI architecture. You will lead the development of advanced data-driven models and design autonomous, multi-agent workflows that solve complex business challenges, automate intricate workflows, and drive deep insights for our MLS subscribers.

• Work with large and complex real estate data sets to extract meaningful insights and solve a wide array of challenging problems using advanced statistical, machine learning, and large language model (LLM) approaches.
• Apply predictive and quantitative analysis, data mining, and experimentation to develop strategies for our product, reporting, and research teams.
• Innovate, define, understand, design, and build prototypes of traditional ML models and autonomous, multi-agent AI systems to drive our product roadmap.
• Architect and deploy robust AI Agentic workflows capable of task planning, recursive reasoning, tool usage, and self-reflection to automate complex real estate processes.
• Hands-on development of end-to-end MLOps and LLMOps pipelines , including dataset curation, model training, prompt engineering, agent trace evaluation, testing, and production deployment.
• Continuously refine and optimize traditional ML models and agentic architectures (e.g., via prompt optimization frameworks like DSPy) to maximize accuracy and minimize hallucinations.
• Develop methodologies for evaluating both predictive model performance and generative agent compliance, utilizing A/B testing, cross-validation, and LLM-as-a-judge evaluation frameworks .
• Partner with Product, Engineering, Research, and other cross-functional teams to translate business needs into scalable, secure AI-driven solutions.
• Stay up-to-date with cutting-edge MLOps, LLMOps, and Agentic AI technologies.

• Experience:
  
  5+ years of hands-on experience in data science, analytics, machine learning, and AI engineering.
• Core
  
  Languages:
  
  Expert in SQL and advanced SQL, and highly proficient in production-grade Python.
• Traditional ML Ecosystem:
  Proficient in frameworks, tools, and libraries such as Tensor Flow, PyTorch, scikit-learn, Pandas, and Jupyter Notebook.
• Agentic AI Frameworks:
  Proven experience building stateful, multi-agent workflows using Lang Chain, Lang Graph, CrewAI, Llama Index Workflows , or the Microsoft Agent Framework .
• Enterprise Agent Platforms:
  Hands-on experience using enterprise-grade agent development and orchestration platforms, specifically Dataiku (utilizing Dataiku LLM Mesh & Agent Hub) or Google Cloud's Gemini Enterprise Agent Platform (formerly Vertex AI Agent Builder) to build, run, and govern production-ready AI agents.
• Integrations & Protocols:
  Solid proficiency with building API integrations, advanced Function Calling, and working with the Model Context Protocol (MCP) to seamlessly connect LLMs to external databases and software tools.
• Data & Knowledge Retrieval:
  Strong data manipulation, wrangling, and mining skills paired with a deep understanding of Vector Databases (e.g., Pinecone, Qdrant, Milvus) and advanced Retrieval-Augmented Generation (RAG and GraphRAG).
• AI Security:
  Deep understanding of LLM vulnerabilities, including prompt injection mitigation , jailbreak prevention, and the implementation of…