Python Gen AI Developer - ZL

Job Description

Top 5 Technical Skills:

1. Python
2. Gen AI
3. SQL
4. AWS Data Services
5. LLM
6. ML
7. Sagemaker
8. Bedrock

Top 3 Soft Skills:

1. Confidence in Communication skills for Teamwork and sharing
2. Stand alone to get work done, Independent
3. Flexibility

Company / Project Description / Business Driver

Enter Overview of client, project description and the business drivers

Job Description:
Experience:
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

Key Responsibilities:
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 compliance

Required Qualifications:
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.

Preferred Qualifications:
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.