Gen AI developer

Virtusa; Irving (TX); On-site; USD 120,000 - 190,000; Full time

Job summary

Virtusa is seeking a skilled AI Engineer to lead the design, development, and deployment of Python-based Generative AI solutions, including RAG systems and conversational agents such as Claude.

The role focuses on architecting scalable AI/ML workflows, deploying models to production, and integrating services across Multi-Cloud Platforms with enterprise data sources like Oracle databases. You will work in an Agile team to deliver reliable AI features and optimize performance.

Qualifications

• Experience building Python-based AI/ML solutions.
• Familiarity with Retrieval-Augmented Generation architectures.
• Ability to design scalable AI/ML workflows for training to production.
• Experience with cloud and on-premise service integration.

Responsibilities

• Lead design, development, and deployment of Python and Gen AI solutions including RAG systems and conversational agents.
• Architect scalable AI/ML workflows from training to production deployment.
• Develop and integrate services with Multi-Cloud Platforms across enterprise environments.
• Build data integration pipelines connecting AI models with Oracle databases.
• Apply software design patterns to deliver modular, high-performance code.
• Drive Gen AI innovation and push capabilities for financial forecasting.
• Collaborate in Agile teams to translate requirements into reliable AI features.
• Champion performance improvements and system optimization.

Skills

Python

Generative AI

RAG architectures

Conversational AI

Tools

Claude

Oracle

Job description

Lead the design, development, and deployment of Python and Generative AI solutions, including sophisticated Retrieval-Augmented Generation (RAG) architectures and conversational AI agents using models like Claude.

Architect and implement scalable AI/ML workflows, managing the end-to-end lifecycle of models from training to production deployment.

Develop and integrate services with Multi-Cloud Platforms (MCPs), ensuring seamless operation and communication between different cloud environments and on-premise systems.

Build robust data integration pipelines to connect AI models with enterprise data sources, including large-scale Oracle databases.

Apply deep knowledge of software design patterns and Python best practices to create modular, high-performance, and maintainable code.

Actively drive innovation by exploring and implementing the latest advancements in Gen AI, pushing the boundaries of what's possible in financial forecasting.

Collaborate in an Agile environment with cross-functional teams to translate complex business requirements into powerful and reliable AI features.

Champion performance improvement and system optimization, ensuring our AI solutions are both powerful and efficient.