Python Developer

This app is an internal GenAl platform designed to support building and deploying Al-powered tools and agents. It provides infrastructure and components for working with large language models (LLMs), integrating various data sources, and orchestrating intelligent workflows. The platform includes tools for managing prompt templates, configuring model pipelines, handling input/output processing, and deploying modular Al services. It supports both open-source and commercial LLMs (e.g., OpenAl, Anthropic), and can run across multiple cloud environments. App AI is used across the organization to create custom Al assistants, automations, and decision support systems - typically combining structured business data with LLMs to generate insights, recommendations, and actions. It also includes role-based access controls, audit logging, and API integrations to ensure enterprise compliance and scalability. App AI is applied across industries such as: Healthcare: Accelerates insights from medical data. Aviation: Analyzes customer feedback to improve services. Retail: Generates personalized marketing content. Finance: Automates contract workflows and compliance processes

Typical Tasks for Python Developers 

* Build modular Python services for parsing, analyzing, and routing incoming medical and insurance documents. 

* Design and maintain custom pipelines for PDF processing, layout extraction, and field mapping using tools like pdfplumber, PyMuPDF, and heuristic matching. 

* Develop integrations with third-party APIs for document retrieval, submission, and status tracking (e.g., eFax, Athenahealth). 

* Implement and benchmark different approaches for matching patient and provider identities across unstructured data sources. 

* Create and maintain internal tools for debugging document flows and visualizing extracted metadata. 

* Automate QA checks for document classification and extraction results, reducing manual validation by >30%. 

* Prototype and deploy semantic search features using vector databases and hybrid retrieval methods. 

* Build health-check dashboards and job monitors to track performance and reliability of ingestion services. 

* Collaborate with ML and product teams to define input/output specs for document annotation and pre-processing steps. 

* Contribute to CI/CD setup, containerization, and environment management for Python services (Docker, GitHub Actions).

We offer:

• Attractive financial package

• Challenging projects

• Professional & career growth

• Great atmosphere in a friendly small team