Data Science Engineer / AI Agent Systems Engineer

We’re looking for an experienced engineer to join our team and work on building production-ready AI systems. This role is perfect for someone who enjoys combining AI/ML expertise with solid software engineering practices to deliver real-world solutions.

Requirements:

- AI/ML: 2+ years hands-on with LLM APIs, production deployment of at least one AI system

- Experience with LangChain, CrewAI, or AutoGen (one is enough)

- Understanding of prompt engineering (Chain-of-Thought, ReAct) and tool/function calling

- Python: 3+ years experience, strong fundamentals, Flask/FastAPI, async/await, REST APIs

- Production Experience: built systems running in production, handled logging, testing, error handling

- Cloud experience with AWS / GCP / Azure (one is enough)

- Familiar with Git, CI/CD, databases (PostgreSQL/MySQL)

Nice to Have:

Experience with vector databases (Pinecone, Weaviate)

Docker/containerization knowledge

Fintech or financial services background

Advanced ML/AI education or certifications

What You’ll Work On:

- Designing and deploying AI-powered systems using LLMs (OpenAI, Anthropic, etc.)

- Building agent-based solutions with frameworks like LangChain, CrewAI, or AutoGen

- Integrating AI systems with external APIs, databases, and production services

- Writing clean, tested Python code and deploying services to the cloud

- Collaborating with stakeholders to translate business requirements into technical solutions

Project

A system for automating accounting operations for companies, which reads, analyzes, compares, and interacts with accounting data. The goal is to make processes faster, more accurate, and scalable, minimize manual work, and increase client efficiency.

Project stage: MVP is nearly complete; the next step is to automate the MVP and scale the product.