Gen AI
Virtusa.com
Office
AP
Full Time
Gen AI - (CREQ231704)
Qualifications & Required Experience
Strong programming skills in Python, with hands-on experience developing APIs and services using Flask.
Proficiency in React.js for building intuitive and responsive front-end interfaces.
Solid experience in Generative AI (GenAI) and LLM-based NLP applications, leveraging tools such as:
- LangChain and Retrieval-Augmented Generation (RAG) patterns
- Hugging Face Transformers
- Prompt tuning, parameter optimization, and accuracy enhancement techniques
Practical experience with Amazon Bedrock, including integration with Claude, Titan embeddings, and other foundation models.
Knowledge of RAG evaluation frameworks, such as RAGAS and TruLens, for model evaluation and benchmarking.
Experience with vector databases (e.g., OpenSearch) for semantic search and embedding storage.
Working knowledge of NoSQL/document databases, especially Amazon DynamoDB.
Strong understanding of data modeling principles and best practices.
Proven ability to collaborate with cross-functional stakeholders and clearly articulate model accuracy issues along with remediation strategies.
Preferred Experience (Nice to Have)
Experience designing and developing machine learning models and training pipelines.
Familiarity with microservices architecture, and implementation using RESTful services.
Hands-on experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
Exposure to cloud computing and distributed systems, including Kubernetes, Docker, and AWS Cloud Services, S3.
Description
Job Description: GenAI/MLE DeveloperQualifications & Required Experience
Strong programming skills in Python, with hands-on experience developing APIs and services using Flask.
Proficiency in React.js for building intuitive and responsive front-end interfaces.
Solid experience in Generative AI (GenAI) and LLM-based NLP applications, leveraging tools such as:
- LangChain and Retrieval-Augmented Generation (RAG) patterns
- Hugging Face Transformers
- Prompt tuning, parameter optimization, and accuracy enhancement techniques
Practical experience with Amazon Bedrock, including integration with Claude, Titan embeddings, and other foundation models.
Knowledge of RAG evaluation frameworks, such as RAGAS and TruLens, for model evaluation and benchmarking.
Experience with vector databases (e.g., OpenSearch) for semantic search and embedding storage.
Working knowledge of NoSQL/document databases, especially Amazon DynamoDB.
Strong understanding of data modeling principles and best practices.
Proven ability to collaborate with cross-functional stakeholders and clearly articulate model accuracy issues along with remediation strategies.
Preferred Experience (Nice to Have)
Experience designing and developing machine learning models and training pipelines.
Familiarity with microservices architecture, and implementation using RESTful services.
Hands-on experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
Exposure to cloud computing and distributed systems, including Kubernetes, Docker, and AWS Cloud Services, S3.
Primary Location
: IN-AP-HyderabadSchedule
: Full TimeEmployee Status
: Individual ContributorJob Type
: ExperiencedTravel
: NoJob Posting
: 17/09/2025, 11:27:38 AMGen AI
Office
AP
Full Time
September 17, 2025