Senior Data Scientist BN_28/10/2026

Margo Group; Warszawa; Hybrid; PLN 300,000 - 520,000; Full time

Job summary

Margo Group in Poland seeks a senior AI/ML software engineer to design and develop LLM-based agentic solutions for the Investment Banking division. You will work with business teams to implement data extraction pipelines, evaluate AI agents, and deploy models on GPU infrastructure with testing and DevOps best practices.

The role requires strong Python, OO programming, FastAPI, and experience with asynchronous microservices, LangGraph, DSPy, and vLLM.

Qualifications

• Strong Python with extensive experience in Object-Oriented programming and enterprise design patterns.
• Proven track record building asynchronous microservices and endpoints using FastAPI.
• Hands-on pytest for unit, functional, and integration testing for ML/LLM pipelines.
• Bash scripts for automation, data handling, and container interaction.

Responsibilities

• Design and develop LLM-based agentic solutions to automate complex business processes.
• Work closely with business teams to identify needs and drive adoption of AI solutions.
• Develop data extraction pipelines and implement evaluation and observability frameworks for AI agents.
• Deploy and industrialize models (LLMs, GPUs), ensuring quality through testing and DevOps best practices.
• You are taking full ownership in driving AI features.
• You remember to respect the boundaries and non-deterministic nature of LLMs, communicate constraints clearly, and build robust safety rails.
• You are a team player, communicate trade-offs with architects and business users, and mentor peers.
• You are testing ideas and PoCs quickly, validate feasibility with data and avoid technical debt.

Skills

Python programming

Object-oriented programming

Enterprise software design patterns

Tools

FastAPI

pytest

Bash scripting

LangGraph

DSPy

vLLM

CUDA

Kubernetes

Jenkins

Arize Phoenix

Google ADK

Job description

Context:

A team responsible for the development and industrialization of applications for the Investment Banking division. Accelerating the integration of generative AI solutions and AI agents into business processes. A strategic environment within the platform, with high-impact use cases in document analysis, credit, and finance.

Expectations:

• Strong Python with extensive experience in Object-Oriented Programming and enterprise software design patterns.
• Proven track record building asynchronous microservices and endpoints using FastAPI.
• Hands-on practice in pytest (unit, functional, and integration testing for ML/LLM pipelines).
• Bash scripts for automation, data handling, and container interaction.

• LLMs Architecture understanding proven by project portfolio.
• Architecting multi-step, stateful agentic graphs using LangGraph or Google ADK.
• Hands-on experience optimizing LLM pipelines programmatically using DSPy.
• Practical knowledge of deploying and running high-throughput open-weight models on GPU infrastructure using runtimes such as vLLM (experience with CUDA and fine-tuning is a strong plus).

• Hands-on familiarity with automated build, test, and release pipelines (Jenkins).
• Experience setting up tracing, drift detection, and automated evaluations for generative workflows using tools like Phoenix Arize.
• Dedication to shipping stable, secure code into flagship banking infrastructure where compliance, auditability, and data security are non-negotiable.
• General Stack: Google ADK, LangGraph, DSPy, vLLM, FastAPI, Python, Pytest. Arize Phoenix. Kubernetes, Jenkins, GPUs.

Responsibilities:

• Design and develop LLM-based agentic solutions to automate complex business processes.
• Work closely with business teams to identify needs and drive the adoption of AI solutions.
• Develop data extraction pipelines and implement evaluation and observability frameworks for AI agents.
• Deploy and industrialize models (LLMs, GPUs), ensuring quality through testing and DevOps best practices
• You are taking full ownership in driving AI features.
• You remember to respect the boundaries and non-deterministic nature of LLMs, communicate constraints clearly, and build robust safety rails.
• You are a team player, communicate technical trade-offs cleanly with architects and business users, and enjoy mentoring peers.
• You are testing ideas and PoCs quickly, validate feasibility with data and avoid technical debt.

Career Prospects:

• Build expertise in Agentic AI architectures and the industrialization of LLMs in production. Work on high-visibility projects within the Investment Banking division.