Senior GenAI Engineer – AWS & SageMaker

Job Summary

We are seeking a highly skilled Senior GenAI Engineer with strong expertise in AWS, Python, SageMaker, and Large Language Models (LLMs) to support enterprise AI initiatives within a fast-paced financial services environment. The ideal candidate will have experience designing and deploying AI/ML solutions, building scalable data pipelines, and developing GenAI-powered applications using modern AWS cloud services.

This role requires someone who can work independently, communicate confidently with cross-functional teams, and contribute to building production-ready AI systems focused on financial reporting, summarization, analytics, and intelligent automation.

Key Responsibilities

• Design, develop, and deploy Generative AI and machine learning solutions using AWS SageMaker and related AWS services.
• Build and optimize prompt engineering strategies for LLM-based financial reporting, summarization, and communication workflows.
• Develop scalable ETL/data pipelines using Python and SQL to process structured and unstructured financial datasets.
• Work with Large Language Models (LLMs) including Anthropic Claude/Sonnet and other foundation models.
• Implement Retrieval-Augmented Generation (RAG) workflows and vector-based retrieval systems where applicable.
• Collaborate with business stakeholders, analysts, and engineering teams to translate business needs into AI-driven solutions.
• Monitor model performance, improve prompt quality, and optimize inference workflows for accuracy and efficiency.
• Build reusable AI/ML components and maintain documentation for workflows, models, and deployment strategies.
• Support model deployment, experimentation, and lifecycle management within AWS cloud environments.

Required Skills

• 8+ years of overall software engineering experience
• 2+ years of hands-on AI/ML or Generative AI engineering experience
• Strong expertise in Python and SQL
• Hands-on experience with AWS services including SageMaker, S3, Lambda, and Redshift
• Experience working with LLMs, prompt engineering, and GenAI applications
• Strong understanding of machine learning workflows and model deployment
• Experience developing scalable data processing pipelines
• Excellent communication and collaboration skills
• Ability to work independently in a fast-paced environment

Preferred Skills

• Experience with AWS Bedrock
• Experience with RAG architectures and vector databases such as FAISS or Pinecone
• Exposure to MLOps and model lifecycle management
• Experience in financial services or fintech environments
• Familiarity with data visualization tools such as Tableau or Power BI

Education

Bachelor’s degree in Computer Science, Data Science, Engineering, Finance, or related field.