Senior Technology Architect - AI/GenAI- Q3 FY 26

Job Overview:

• Develop and design enterprise-level Generative AI solutions utilizing Python and contemporary AI frameworks.
• Create AI applications that leverage LLMs, including embedding prompts, function calling, and agentic AI methodologies.
• Establish Retrieval Augmented Generation (RAG) pipelines for enterprise knowledge acquisition and generation scenarios.
• Architect comprehensive AI solutions encompassing:
• o Data ingestion
• o Data processing
• o Retrieval
• o Generation
• o Evaluation
• Collaborate with Agentic AI frameworks such as CrewAI, LangChain, LangGraph, LlamaIndex, AutoGen, and Langfuse.
• Utilize prompt engineering techniques to enhance the accuracy, reliability, and usability of LLMs.
• Assess the appropriateness of fine-tuning versus RAG based on both business and technical criteria.
• Facilitate LLM fine-tuning processes, including instruction tuning and supervised fine-tuning.
• Oversee data preparation for fine-tuning, ensuring effective training and validation splits, data quality assessments, and contamination prevention.
• Deploy AI workloads on cloud services like Azure, AWS, or GCP.
• Containerize AI applications using Docker and have a fundamental understanding of Kubernetes.
• Implement model engineering best practices to create scalable, reliable, and production-ready AI systems.

Core Responsibilities:

• We seek a proficient Generative AI Engineer/Senior Technologist with substantial hands-on expertise in Python, Large Language Models, RAG, Agentic AI, fine-tuning, and cloud deployment.
• The preferred candidate will possess a thorough understanding of LLM architectures from a systems perspective, with the capability to design, construct, deploy, and assess end-to-end AI solutions for enterprise applications.
• This position demands strong engineering skills, adept problem-solving abilities, and practical experience with modern AI frameworks, cloud-native deployments, and model engineering principles.

Desired Qualifications:

• Technology -> AI-AI Engineering -> AI/ML Solution Architecture and Design -> Generative AI
• Technology -> AI-AI Engineering -> MLOps
• Technology -> AI-AI Engineering -> LLMOps