Senior Engineer (hybrid AI Systems / Machine Learning)

We are hiring a Senior AI/ML Engineer to build, improve, and productionize all AI components of the platform. This engineer will work closely with backend engineers and founders to design robust, scalable, and auditable AI pipelines.

You will own
- document classification pipelines
- document data extraction
- financial reasoning models
- underwriting decision support
- LLM flows, tool use, and retrieval
- Python microservices supporting the AI stack

This is a role for someone who can take AI systems from idea - to prototype - to production-grade service.

About the project

The product builds production-grade AI assistants for loan officers, processors, and underwriters. The platform ingests lender documents, classifies and extracts structured data, computes metrics/risk signals, and powers decisioning flows that integrate with existing LOS/CRM systems. 

Key Responsibilities
- Build and optimize AI pipelines for document classification, data extraction, summarization, and reasoning
- Work with LangChain, DSPy to orchestrate LLM logic
- Wrap models into Python microservices that integrate with the main TS backend
- Implement model monitoring: confidence scores, hallucination detection, stability
- Optimize model performance for speed, cost, and reliability
- Build data pipelines for preprocessing documents, extracting entities, and transforming financial information
- Integrate AI pipelines with queue systems (RabbitMQ or similar).
- Design workflows in cooperation with Temporal or equivalent orchestrators
- Ensure Python services work seamlessly with the Node.js backend.
- Ensure the platform meets enterprise-grade reliability and compliance standards

Core Technical Skills
- 4+ years experience in Machine Learning / AI engineering.
- Expert in Python and ML/AI frameworks.
- Strong hands-on experience with LLMs, OCR, NLP, or document intelligence.
- Experience building production AI pipelines (not just prompt engineering).
- Familiarity with: LangChain, DSPy, RAG, Tool-using agents
- Practical experience integrating LLMs with structured data 
- Experience building scalable AI microservices.
- Familiar with queues (RabbitMQ / Kafka), event systems, or workflow orchestrators.
- Understanding of AWS, Kubernetes (EKS), Docker, CI/CD.
- Ability to design reliable long-running background jobs and multi-step ML workflows.