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Senior AI Engineer (Python)

Roles & Responsibilities

  • Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field, with a strong emphasis on AI and machine learning.
  • Proven experience in data science, machine learning engineering, and NLP; English B2 Upper Intermediate.
  • Proficiency in Python and experience with data science libraries; experience with prompt engineering and fine-tuning large language models.
  • Experience with LangGraph and LangChain; familiarity with SQL; experience with Model Context Protocol (MCP) and Text-to-SQL (NL2SQL).

Requirements:

  • Implement NLP solutions to develop features for a financial software platform using Python.
  • Create, refine, and optimize prompts for generative AI models to achieve desired outputs for various financial use cases.
  • Build NLP-based data extraction systems to retrieve data from databases and integrate it into workflows.
  • Develop and maintain API integrations and leverage generative AI to automate the generation of detailed financial reports.

Job description

The role focuses on building and optimizing AI solutions by integrating data from multiple systems and collaborating with architects and analysts to deliver high-quality dataset.

Role description:

Implement NLP Solutions: Utilize NLP models to develop features for a financial software platform using Python.

Prompt Engineering: Create, refine, and optimize prompts for generative AI models to achieve desired outputs for various financial use cases.

Data Extraction: Build systems to extract relevant data from databases using NLP techniques and integrate this data into workflows.

API Integration: Develop and maintain integrations with various APIs to enhance the capabilities of the NLP assistant.

Automated Report Generation: Utilize generative AI to automate the creation of detailed and accurate financial reports.

Collaboration and Communication: Work closely with software engineers, business analysts, and other stakeholders to understand requirements and deliver high-quality solutions.

Continuous Improvement: Stay up to date with the latest advancements in NLP and generative AI to continuously improve the assistant's capabilities.

Qualifications:

Education: Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field, with a strong emphasis on AI and machine learning.

Experience: Proven experience in data science, machine learning engineering, and NLP.

Proficiency in Python and experience with data science libraries.

Experience with prompt engineering and fine-tuning large language models.

Experience in LangGraph and LangChain.

Familiarity with SQL.

Experience with Model Context Protocol (MCP) standard.

Experience with Text-to-SQL (NL2SQL).

• English B2 Upper Intermediate

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