Data Scientist
Core
Building, integrating, and deploying generative AI systems and agentic workflows into production-grade cloud applications.
Role type
Entry-level AI Engineer (GenAI/MLOps)
Builds
Production-ready GenAI applications, RAG systems, multi-agent frameworks, and scalable inference pipelines.
Domain
Financial derivatives markets / Generative AI / Cloud Infrastructure
Deliverable
production ML models | product features | infrastructure
Required skills
Python, backend software engineering, GCP (Cloud Run, GKE, BigQuery), Git, CI/CD, foundation model APIs (Gemini, OpenAI, Anthropic), vector databases
Preferred skills
LangChain, LlamaIndex, Google ADK, observability tools, financial markets knowledge
Technologies
Python, GCP, Kubernetes, BigQuery, LangChain, LlamaIndex, GitHub Copilot, Cursor
Responsibilities
Write, test, and deploy GenAI applications; build backend pipelines for RAG and multi-agent systems; maintain CI/CD pipelines for ML models; optimize model inference and cloud costs; develop data processing and embedding pipelines; use AI coding assistants for development.
Seniority
Entry-level, hands-on IC
