Key Responsibilities
GenAI Solutioning & Architectural Design Lead the design and implementation of end-to-end Generative AI solutions, ensuring scalable, robust, and efficient architecture that aligns with business needs.
Data Strategy & Management Develop and execute strategies for data collection, cleaning, transformation, and integration for AI model development. Apply best practices for data pipeline design and optimization.
AI Agents Development Design and implement intelligent AI agents using advanced techniques in NLP and machine learning to improve automation, user interaction, and decision-making processes.Fine-tuning & Prompt Engineering Fine-tune pre-trained models (e.g., GPT, BERT, etc.) and optimize prompt engineering techniques to drive high-quality, actionable outputs for diverse business use cases.
Machine Learning & Deep Learning Models Build, train, and deploy machine learning models, including deep learning models, for complex AI applications across various domains.
LLM Provisioning from CSPs Lead the provisioning and customization of Large Language Models (LLMs) from major Cloud Service Providers (CSPs) such as Azure, AWS, and Google Cloud, ensuring optimal performance and cost-effectiveness.
Technologies & Frameworks Utilize Langchain, CrewAI, and VectorDB for building, integrating, and scaling NLP solutions, and leverage Flask/FastAPI for model deployment and integration.
Database & SQL Management Work with databases (SQL/NoSQL) for data storage, querying, and management to support AI model development and deployment.Tokenization & NLP Techniques Apply advanced tokenization techniques to preprocess and analyze data for NLP tasks, enhancing model efficiency and performance.
Deployment & Evaluation Oversee the deployment of AI models, ensuring smooth integration with production systems, and perform rigorous evaluation of LLMs for accuracy, efficiency, and scalability.
Required Skills & Qualifications
Proven experience in GenAI solutioning and architectural design for large-scale AI systems.
Expertise in data cleaning, transformation, and data strategy to drive AI and machine learning initiatives.
Strong hands-on experience with AI agents, prompt engineering, and fine-tuning LLMs for business applications.
Proficiency in machine learning models, deep learning techniques, and NLP applications.
Deep knowledge of LLM provisioning from different Cloud Service Providers (CSPs) (e.g., AWS, Azure, Google Cloud).
Experience with Langchain, CrewAI, VectorDB, Flask, FastAPI, and related frameworks for model integration and deployment.Strong database skills, with proficiency in SQL and experience in working with NoSQL databases.
Familiarity with advanced tokenization techniques and their applications in NLP.
Experience with model deployment, integration, and LLM evaluation for real-world applications.
We are seeking a highly skilled GenAI Solution Architect to join our growing team. In this role, you will leverage your expertise in Generative AI, machine learning, and natural language processing (NLP) to design and implement innovative AI-driven solutions. The ideal candidate will have a deep understanding of architectural design, data strategies, AI agents, and the latest advancements in language models. You will play a key role in delivering cutting-edge solutions, working with large-scale data, and building systems that enhance automation, intelligence, and efficiency for our clients.
Key Responsibilities
GenAI Solutioning & Architectural Design Lead the design and implementation of end-to-end Generative AI solutions, ensuring scalable, robust, and efficient architecture that aligns with business needs.
Data Strategy & Management Develop and execute strategies for data collection, cleaning, transformation, and integration for AI model development. Apply best practices for data pipeline design and optimization.
AI Agents Development Design and implement intelligent AI agents using advanced techniques in NLP and machine learning to improve automation, user interaction, and decision-making processes.Fine-tuning & Prompt Engineering Fine-tune pre-trained models (e.g., GPT, BERT, etc.) and optimize prompt engineering techniques to drive high-quality, actionable outputs for diverse business use cases.
Machine Learning & Deep Learning Models Build, train, and deploy machine learning models, including deep learning models, for complex AI applications across various domains.
LLM Provisioning from CSPs Lead the provisioning and customization of Large Language Models (LLMs) from major Cloud Service Providers (CSPs) such as Azure, AWS, and Google Cloud, ensuring optimal performance and cost-effectiveness.
Technologies & Frameworks Utilize Langchain, CrewAI, and VectorDB for building, integrating, and scaling NLP solutions, and leverage Flask/FastAPI for model deployment and integration.
Database & SQL Management Work with databases (SQL/NoSQL) for data storage, querying, and management to support AI model development and deployment.Tokenization & NLP Techniques Apply advanced tokenization techniques to preprocess and analyze data for NLP tasks, enhancing model efficiency and performance.
Deployment & Evaluation Oversee the deployment of AI models, ensuring smooth integration with production systems, and perform rigorous evaluation of LLMs for accuracy, efficiency, and scalability.
Required Skills & Qualifications
Proven experience in GenAI solutioning and architectural design for large-scale AI systems.
Expertise in data cleaning, transformation, and data strategy to drive AI and machine learning initiatives.
Strong hands-on experience with AI agents, prompt engineering, and fine-tuning LLMs for business applications.
Proficiency in machine learning models, deep learning techniques, and NLP applications.
Deep knowledge of LLM provisioning from different Cloud Service Providers (CSPs) (e.g., AWS, Azure, Google Cloud).
Experience with Langchain, CrewAI, VectorDB, Flask, FastAPI, and related frameworks for model integration and deployment.Strong database skills, with proficiency in SQL and experience in working with NoSQL databases.
Familiarity with advanced tokenization techniques and their applications in NLP.
Experience with model deployment, integration, and LLM evaluation for real-world applications.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
Learn more
Awards and recognition
Syncing your Virtusa Information
Syncing Complete
Exporting your personal Virtusa brand items
Export Complete
Check your downloads folder for files and implementation instructions.
Assets are now available in your profile for future editing and use.
Loading your existing headshots
Please select any one of the images below
Downloading Secure Assets
Signing out