Data Scientist

LLM Data Scientist

We are looking for a talented LLM Data Scientist to join a fast-growing AI product team building advanced systems that transform complex business data into actionable insights.

This role focuses on designing and deploying LLM-powered reasoning systems, multi-agent workflows, and structured knowledge architectures that support real-world decision making. You will work closely with engineers and product teams to bring cutting-edge AI capabilities into a production environment.

What You'll Do:

Build Multi-Agent AI Systems

Design and implement agent-based workflows using orchestration frameworks such as LangGraph. Develop reasoning pipelines, tool-usage logic, and memory components as part of the AI architecture.

Develop Structured Knowledge Layers

Contribute to building structured knowledge systems that connect financial and operational data to support AI-driven reasoning and analytics.

Integrate and Adapt LLMs

Work with both API-based and open-source LLMs (e.g., Llama, Mistral). Participate in model selection, reliability improvements, and domain adaptation, including fine-tuning approaches such as LoRA / PEFT when relevant.

Implement Context & Memory Systems

Develop mechanisms for context injection, retrieval, and memory usage across agent workflows. Support grounding through structured queries, document retrieval, and knowledge lookups.

Production Integration

Collaborate with engineering teams to integrate AI components into cloud infrastructure (GCP / Vertex AI) while ensuring scalability, reliability, and performance.

Drive Innovation

Stay up to date with emerging developments in agent-based systems, structured knowledge architectures, and open-source LLMs, and help bring impactful improvements into the platform.

Requirements:

3+ years of experience building production-grade AI/ML systems in Python

Hands-on experience building LLM-powered applications and working with orchestration frameworks (LangGraph or similar)

Experience integrating API-based and open-source LLM models

Familiarity with fine-tuning approaches such as LoRA / PEFT

Strong understanding of retrieval systems, embeddings, context injection, and multi-source data integration

Solid SQL and data modeling skills

Experience deploying AI systems in cloud environments (GCP preferred)

Strong system design mindset and ability to translate product requirements into scalable AI solutions

Ability to independently solve complex problems and translate ambiguous business questions into structured data science projects

Nice to Have:

Experience building multi-agent AI systems in production

Experience with GCP services such as Firestore, Cloud Functions, or Vertex AI

Background in financial analytics, time-series modeling, or real estate data

Experience working with complex multi-source data environments

Familiarity with data governance, privacy, and security standards for sensitive financial data

If you're excited about building real-world AI systems powered by LLMs and multi-agent architectures, we'd love to hear from you.