Principal Technologist- Q3 FY 27

Job Overview:

• This position is centered on our key clients who are undertaking digital transformation projects.
• The role necessitates close collaboration with sales and delivery teams to formulate solutions for extensive and intricate programs, pinpoint significant technology opportunities, create solution propositions, prototype them, and bring them to market.
• This position requires networking and working collaboratively with Chief Digital Officers (CDOs) as well as digital and business leaders within client organizations to develop insights on industry trends and digital technology influences affecting enterprises.

Primary Responsibilities:

• This position is centered on our key clients who are undertaking digital transformation projects.
• The role necessitates close collaboration with sales and delivery teams to formulate solutions for extensive and intricate programs, pinpoint significant technology opportunities, create solution propositions, prototype them, and bring them to market.
• This position requires networking and working collaboratively with Chief Digital Officers (CDOs) as well as digital and business leaders within client organizations to develop insights on industry trends and digital technology influences affecting enterprises.
• Design and implement enterprise-grade Generative AI solutions utilizing Python and contemporary AI frameworks.
• Develop AI applications leveraging LLMs, embeddings, prompt engineering, tool utilization, and agentic AI methodologies.
• Establish Retrieval Augmented Generation (RAG) pipelines for enterprise-level knowledge retrieval and generation applications.
• Craft comprehensive AI solutions that encompass:
• o Data ingestion
• o Data processing
• o Retrieval
• o Generation
• o Evaluation
• Utilize Agentic AI frameworks such as CrewAI, LangChain, LangGraph, LlamaIndex, AutoGen, and Langfuse.
• Implement prompt engineering techniques to enhance the accuracy, reliability, and usability of LLMs.
• Assess the appropriateness of fine-tuning versus RAG based on specific business and technical requirements.
• Assist in LLM fine-tuning workflows, including instruction tuning and supervised fine-tuning processes.
• Oversee data preparation for fine-tuning, including train-validation splits, data quality assessments, and contamination prevention measures.
• Deploy AI workloads on cloud platforms such as Azure, AWS, or GCP.
• Containerize AI applications using Docker and possess foundational knowledge of Kubernetes concepts.
• Adopt model engineering best practices to ensure scalable, reliable, and production-ready AI systems.

Desired Skills:

Technology->Java->Core Java, Technology->AI-Responsible AI->Responsible AI->ethical ai, Technology->OpenSystem->Python - OpenSystem->Python