Note: The job is a remote job and is open to candidates in USA. Bright MLS is a leading data technology company and the largest multiple listing service in the United States, focused on creating an open, clear, and competitive housing market. The Predictive & Agentic AI Engineer will develop predictive machine learning models and autonomous multi-agent generative AI workflows, while building MLOps and LLMOps pipelines to solve complex real estate challenges. The role partners with cross-functional teams to deliver scalable, secure, and production-ready AI solutions.
Responsibilities
- 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
Skills
- 5+ years of hands-on experience in data science, analytics, machine learning, and AI engineering
- Expert in SQL and advanced SQL, and highly proficient in production-grade Python
- Proficient in frameworks, tools, and libraries such as TensorFlow, PyTorch, scikit-learn, Pandas, and Jupyter Notebook
- Proven experience building stateful, multi-agent workflows using LangChain, LangGraph, CrewAI, LlamaIndex Workflows, or the Microsoft Agent Framework
- 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
- 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
- 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)
- Deep understanding of LLM vulnerabilities, including prompt injection mitigation, jailbreak prevention, and the implementation of safety guardrails (e.g., Guardrails AI, NeMo Guardrails)
- Expert in AWS artificial intelligence/machine learning services, specifically AWS SageMaker and AWS Bedrock, Bedrock AgentCore, alongside Redshift, Comprehend, and Lex
- Familiarity with LLM tracing and observability infrastructure (e.g., LangSmith, Langfuse, or Arize Phoenix) to monitor and debug complex agent loops
- Strong analytical mindset with excellent communication skills to convey intricate technical concepts and agent behaviors effectively to both engineering teams and non-technical business stakeholders
- Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field
- Master's degree or a Ph.D. in a quantitative field is a plus
- AWS Certified Generative AI Developer – Professional certification or equivalent hands-on experience building autonomous agentic systems using Amazon Bedrock Agents and Bedrock Flows
- Experience with serverless deployment architectures, including AWS Lambda or Glue jobs
- AWS Certified Solutions Architect or AWS Certified Machine Learning Specialty is a plus
Benefits
- Eligible for annual performance-based bonuses
- Individual and family health, vision, and dental coverage
- 401(k) plan with employer-matching
- Paid Time Off (PTO) and holidays
Company Overview