Senior Software Engineer – AI / Python

Nice to have

• Experience with XBRL, financial compliance, or regulatory reporting systems.
• Knowledge of investment company operations and SEC filing requirements.
• Familiarity with Retrieval-Augmented Generation (RAG).
• Familiarity with modern web frameworks and full-stack development, preferably .NET.
• Experience scaling systems and optimizing application performance.

What we are Looking for

• 7+ years of software development experience, with demonstrated experience building production-grade systems.
• Strong Python development experience.
• Experience developing Python-based document processing pipelines, including parsing, transformation, and metadata extraction from structured and semi-structured documents.
• Hands-on experience integrating and orchestrating Large Language Models (LLMs) within production applications.
• Experience with prompt engineering, including designing, tuning, and evaluating prompts for:
  • Information extraction
  • Classification
  • Document processing workflows
• Experience building AI-powered applications using LLMs.
• Experience with LLM workflows, including:
  • Prompt orchestration
  • Error handling
  • Result evaluation
• Experience building web applications and REST APIs.
• Familiarity with XML, XHTML, and data transformation pipelines.
• Strong problem-solving skills and ability to work with ambiguity in an early-stage product environment.
• Excellent communication and collaboration skills with cross-functional teams.

Benefits

• Contrato a largo plazo.
• 100% Remoto.
• Vacaciones y PTOs
• Posibilidad de recibir 2 bonos al año.
• 2 revisiones salariales al año.
• Clases de inglés.
• Equipamiento Apple.
• Plataforma de cursos en linea
• Budget para compra de libros.
• Budget para compra de materiales de trabajo
• mucho mas..

What You'll Be Working On

• Building and enhancing Python-based document processing workflows.
• Integrating LLM capabilities into a production web application.
• Designing and refining prompts for financial information extraction and classification.
• Processing structured and semi-structured financial documents and metadata.
• Building and integrating REST APIs.
• Improving reliability, error handling, evaluation, and overall performance of AI workflows.
• Collaborating with cross-functional teams to bring the AI Auto-Tagging platform to production.

We’re building AI Auto-Tagging, a standalone web application designed to automate XBRL tagging for Tailored Shareholder Reports (TSRs) used by investment funds.

The platform uses Large Language Models (LLMs) to identify and tag financial data, including hidden metadata that may not be visible in the document text.

Our goal is to deliver a production-grade solution that reduces manual tagging work from hours to minutes while meeting regulatory and business requirements.