Overview

We are looking for a Software Engineers with a strong background in data engineering and applied AI engineering. This role is part of a dual skill track where deep data engineering expertise is essential and hands on experience with AI enablement is expected. The candidate is expected to work from 8 AM to 5 PM New York Time. Client: Our client is a leading global corporate and investment bank, providing a wide range of financial services to large corporates, financial institutions, and institutional investors across international markets. Project Overview: The project involves migrating production data pipelines from legacy environments into a modern, cloud‑native data platform. The new platform enables domain‑oriented data products, scalable analytics, and embedded governance, with AI‑based tools supporting data quality, anomaly detection, privacy, and compliance.

Responsibilities:
  • Design and develop scalable ETL and ELT data pipelines
  • Build and maintain data orchestration workflows using Apache Airflow or similar tools
  • Collaborate with AI engineers to integrate LLMs into data‑driven applications
  • Develop RAG pipelines using embeddings and vector‑based search
  • Optimize Snowflake data models for performance and cost efficiency
  • Contribute to cloud native application design and deployment
  • Support integration or development of MCP servers where applicable
  • Collaborate closely with product, data, and platform teams
Required Qualifications:
  • Mid‑level candidates with 4+ years and Senior candidates with 10+ years of professional experience in software or data engineering.
  • Strong experience building production-grade data pipelines
  • Experience with Snowflake
  • Hands-on experience with Apache Airflow or similar orchestration tools
  • Solid experience with Snowflake, including data modeling and performance tuning
  • Advanced SQL skills and working knowledge of NoSQL databases
  • Strong Python development experience
  • Experience working in cloud environments Azure, AWS or GCP
Nice To Have:
  • Hands on experience with large language models
  • Experience with retrieval augmented generation patterns
  • Experience with embeddings and vector databases
  • Experience using Streamlit or similar tools for GenAI interfaces
  • Exposure to MCP server development or integration
Note:

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