GenAI Engineer, FinTech AI with LLMs & RAG

Senovo IT Ltd; Polska; On-site; PLN 180,000 - 240,000; Full time

Job summary

Senovo IT Ltd invites an experienced AI Engineer to join a FinTech project focused on designing, developing, and deploying advanced AI solutions. You will work closely with architects, engineers, and business stakeholders to build scalable GenAI applications and intelligent workflows.

The role emphasizes hands-on Python development, building and deploying RAG pipelines, and using LangChain and LangGraph to create scalable AI workflows.

Qualifications

• 6+ years of professional software development experience.
• Strong expertise in Python.
• Hands-on experience with RAG.
• Experience with agentic orchestration frameworks.
• Experience with LangChain (LCH).
• Experience with LangGraph (LG).
• Experience building and deploying production-grade AI applications.

Responsibilities

• Design, develop, and deploy AI-powered applications using Python.
• Build and optimize solutions leveraging Large Language Models (LLMs).
• Develop and maintain Retrieval-Augmented Generation (RAG) pipelines.
• Implement and enhance agent-based AI systems and orchestration frameworks.
• Work with LangChain and LangGraph to create scalable AI workflows.
• Integrate AI solutions into existing enterprise systems and platforms.
• Monitor, evaluate, and improve model performance, quality, and reliability.
• Collaborate with cross-functional teams to translate business requirements into AI solutions.
• Follow best practices for MLOps, testing, security, and production deployment.

Skills

Python

LLMs

RAG

LangChain

LangGraph

Agentic Orchestration

APIs integration

Semantic search

Vector databases

MLOps

Job description

Senovo IT Ltd invites an experienced AI Engineer to join a FinTech project focused on designing, developing, and deploying advanced AI solutions. You will work closely with architects, engineers, and business stakeholders to build scalable GenAI applications and intelligent workflows.

The role emphasizes hands-on Python development, building and deploying RAG pipelines, and using LangChain and LangGraph to create scalable AI workflows.