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.
130 zł - 160 zł an hour
Data Scientist - MID Profile - BN 12/11/26 in Warsaw – pracodawca: Margo Group
Margo Group to doskonały pracodawca, który oferuje wyjątkowe możliwości rozwoju zawodowego w dynamicznym środowisku globalnej instytucji finansowej. Nasza kultura pracy opiera się na współpracy i innowacyjności, a pracownicy mają dostęp do szkoleń oraz programów rozwojowych, które wspierają ich karierę. Pracując w naszym zespole, będziesz miał wpływ na kluczowe procesy oraz możliwość pracy z różnorodnymi partnerami, co czyni tę rolę nie tylko satysfakcjonującą, ale i pełną wyzwań.
