Publié il y a 15 jours
AI Engineer
@ Virtusa
Toronto, Ontario
Résumé des exigences :
- Job Requirements
- Years of Experience: 10-15 Years
- Implement and enhance Retrieval-Augmented Generation (RAG) architectures for enterprise knowledge retrieval and question-answering systems.
- Collaborate with business stakeholders, architects, and engineering teams to translate requirements into AI-driven solutions.
- Experience in AI Engineering is a deal breaker.
- Candidates should possess a strong background in AI technologies and demonstrate the ability to deliver high-quality AI solutions in a collaborative environment.
Source et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-10-29
- Première détection par notre source
- 2026-11-14
- Mise à jour du dossier source
- 2026-11-14
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Virtusa
EIM Senior AI Engineer
Location: PCS CA~TORONTO
Years of Experience: 10-15 Years
Job Summary: We are seeking a highly skilled AI Engineer with strong expertise in Python, SQL, AWS Bedrock, AWS SageMaker, LangGraph, LLM Fine-Tuning, and Retrieval-Augmented Generation (RAG). The ideal candidate will be responsible for designing, developing, and deploying scalable AI/GenAI solutions, building intelligent agents, fine-tuning Large Language Models (LLMs), and implementing enterprise-grade AI applications on AWS.
Responsibilities
- Design, develop, and deploy Generative AI solutions using AWS services.
- Build and optimize AI applications leveraging AWS Bedrock and AWS SageMaker.
- Develop and maintain scalable data pipelines using Python and SQL.
- Implement and enhance Retrieval-Augmented Generation (RAG) architectures for enterprise knowledge retrieval and question-answering systems.
- Fine-tune open-source and foundation LLMs to improve domain-specific performance and accuracy.
- Design and orchestrate multi-step AI workflows using LangGraph and agent-based frameworks.
- Integrate AI models with enterprise applications, APIs, databases, and cloud services.
- Evaluate, monitor, and optimize AI model performance, latency, and cost.
- Collaborate with business stakeholders, architects, and engineering teams to translate requirements into AI-driven solutions.
- Follow MLOps best practices for model deployment, monitoring, and governance.
- Ensure security, scalability, and reliability of AI platforms and services.
- Strong in Python and SQL (Advanced Level: 7 to 10 Years)
- AWS Bedrock
- AWS SageMaker
- LLM fine-tuning
- LangGraph
- RAG (Retrieval-Augmented Generation)
- AWS Certifications (AWS Certified Machine Learning, AWS Solutions Architect, or related certifications)
Experience in AI Engineering is a deal breaker. Candidates should possess a strong background in AI technologies and demonstrate the ability to deliver high-quality AI solutions in a collaborative environment.
Work Experience
10-15Years
Journal
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