Must Have:

• Strong Python skills: Expertise in Python for data exploration, analysis, and development using libraries like Pandas, Matplotlib, and Sci-kit Learn. Experience with Jupyter Notebook for interactive coding.
• NLP expertise: Deep understanding of natural language processing concepts and experience using Hugging Face pipelines for tasks like text classification, generation, and entity extraction.
• LLM experience: Hands-on experience with LLM frameworks like LLamaIndex or Langchain to build semantic search, retrieval-augmented generation (RAG), and hybrid search systems.
• Prompt Engineering: Ability to design and structure prompts for LLMs programmatically using APIs from OpenAI, Vertex AI, or Llama. Familiarity with common prompt engineering patterns.
• Vector Database knowledge: Experience with any vector databases like PineCone, Qdrant, Vespa, or Weaviate for efficient similarity search and retrieval.
• NLP evaluation metrics: Familiarity with common metrics used to evaluate the performance of NLP models, RAG systems particularly for retrieval and generation tasks.
• Azure AI Services experience: Experience with key Azure AI services such as Azure OpenAI Service, Azure AI Search, and Azure Document Intelligence for building intelligent solutions.
• Azure resource management: Proficiency in provisioning, configuring, and managing Azure AI resources, including understanding cost management and security best practices.
• Azure DevOps: Experience integrating Azure AI services into continuous integration and continuous delivery (CI/CD) pipelines for efficient deployment and updates.
• Containerization: Experience with containerized deployments on Azure for scalable and portable AI solutions.

Nice to Have:

• Conversation AI platforms: Familiarity with conversation AI platforms like Kore AI, RASA, Google Dialogflow, or CCAI for building conversational agents and chatbots.
• Approximate Nearest Neighbor libraries: Experience with libraries like FAISS or ANNOY for efficient approximate nearest neighbor search, particularly for large datasets.
• Advanced Prompting techniques: Understanding of advanced prompting techniques like ReAct, Few-shot learning, Chain-of-thought, function calling, and Responsible AI to enhance LLM performance and safety.

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 30,000 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 was founded on principles of equal opportunity for all, and so does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.