Responsibilities :
Solution Development Design and develop AI/GenAI-based solutions for AMS use cases such as ticket analytics, incident summarization, root cause insights, and knowledge automation.
PoC & MVP Development Build Proof of Concepts (PoCs) and Minimum Viable Products (MVPs) to validate AI-driven transformation opportunities.
GenAI Implementation Develop applications using LLMs, RAG architectures, vector databases, and prompt engineering techniques.
Integration Integrate AI solutions with ITSM platforms, enterprise applications, and automation tools.
Optimization Improve model performance using prompt tuning, evaluation frameworks, and feedback loops.
Documentation Maintain technical documentation, solution architecture, and implementation guidelines.
Collaboration Work closely with lead consultants, architects, and development teams to deliver scalable AI solutions.
Technical and Professional Requirements:
Strong programming experience in Python and SQL
Experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Hands-on experience with Generative AI and Large Language Models (LLMs)
Familiarity with LLM frameworks such as LangChain or LlamaIndex
Understanding of RAG architectures, vector databases, embeddings, and prompt engineering
Experience building AI-powered solutions such as chatbots, knowledge assistants, ticket analytics, and summarization tools
Understanding of ITSM platforms (ServiceNow, BMC Remedy, etc.)
Experience integrating AI solutions with automation platforms and APIs
Understanding of data preprocessing, feature engineering, and model evaluation
Familiarity with MLOps concepts and model deployment
