AI Engineer Remote from EU US business hours overlap

VIRTUSA REMOTE 2026-09-16

Strong experience as an AI Engineer / ML Engineer / Software Engineer focused on AI.
Hands-on experience building and productionizing Generative AI solutions.
Strong Python development and API integration skills.
Practical experience with LLMs, RAG, prompt engineering, and AI agents.
Experience working with foundation models and/or Amazon Bedrock.
Understanding of MLOps, cloud architecture, model evaluation, and observability.
Experience integrating AI solutions with enterprise systems and data.
Strong software-engineering mindset and experience delivering production-grade solutions.
Understanding of responsible AI, security, and cost optimization.
English at C1 level, with strong communication skills.
Ability to work remotely from the EU with significant US time-zone overlap.

At Virtusa, every innovator has the potential to transform and lead in a digital world—but unlocking that potential takes more than technology; it takes a trusted partner who combines engineering excellence, creativity, and an AI-first mindset.

Together, we co-create solutions that help businesses grow faster, operate smarter, and make experiences better with technology.

Job Description

This is a remote position.

We are looking for an experienced AI Engineer to design, develop, and integrate AI and Generative AI solutions across patient-access, engagement, and analytics platforms.

The role will focus on building and productionizing AI applications, intelligent agents, automation workflows, and AI-enabled services, while integrating foundation models, enterprise data, applications, and business processes.

This Role requires overlap with US Business hours

,[ Design and develop Generative AI applications and AI-enabled services. , Build and productionize intelligent AI agents and automation workflows., Integrate foundation models, including models available through Amazon Bedrock., Develop scalable Python-based services and APIs., Implement RAG, prompt engineering, and model evaluation practices., Connect AI capabilities with enterprise data sources, applications, APIs, and business processes., Implement solutions that are secure, scalable, observable, and cost-effective., Collaborate with Product, Data Engineering, Software Development, Cloud, SRE, and RunOps teams., Apply strong software engineering, cloud, MLOps, and responsible-AI principles throughout the development lifecycle.] Requirements: AI, Analytics platform, Cloud, SRE, MLOps, Python, API, Security, Communication skills