Python AI Developer - ZL

SES
Washington, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Washington, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data analysis
Code Generation
Computer Programming
ETL
Data Visualization
Python
Machine Learning
Power BI
Software Engineering
SQL Databases
Tableau
Data Processing
Large Language Models
Prompt Engineering
Generative AI
Information Technology
Amazon Web Services (AWS)

Job description

  1. Python
  2. Gen AI
  3. SQL
  4. AWS Data Services
  5. LLM
  6. ML
  7. Sagemaker
  8. Bedrock, Design, test, and refine prompts for large language models (LLMs) to support financial reporting, summarization, and client communication tools. Analyze structured and unstructured financial data using Python and SQL, delivering insights through dashboards and reports. Develop and maintain data pipelines and ETL workflows to support GenAI model training and evaluation. Use AWS SageMaker to build, train, and deploy machine learning and GenAI models. Collaborate with data scientists, analysts, and business stakeholders to align AI solutions with financial objectives. Monitor model performance and iterate on prompt and model design to improve accuracy and relevance. Document workflows, models, and prompt strategies for internal knowledge sharing and complianceRequired Qualifications

Requirements

  1. Confidence in Communication skills for Teamwork and sharing
  2. Stand alone to get work done, Independent
  3. Flexibility, 10+ years overall in Software Engineering disciplines, preferably in the financial services industry 2-3 years of experience in AI engineering roles - ML experience in NTH Strong programming skills in Python, SQL and experience with AWS. Priority Order of Skills is AWS, Gen AI, Python, AI Code Generation, SQL, 2 3 years of experience in data analysis or machine learning roles. Proficiency in Python and SQL for data manipulation and analysis. Hands-on experience with major AWS services, particularly SageMaker, S3, Redshift, and Lambda. Experience working with LLMs (Anthropic Claude, Sonnet) and prompt engineering techniques. Strong understanding of financial data, KPIs, and reporting standards. Excellent communication and collaboration skills., Experience in the finance or fintech industry. Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG). Exposure to data visualization tools (e.g., Power BI, Tableau). Bachelor s degree in Computer Science, Data Science, Finance, or a related field.

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