MLops, Natural Language Processing, Data Warehousing, Computer Vision, Deep Learning, Data lakes, Infrastructure as Code, DevOps practices, ETL processes, AI ML technologies, CI CD

System integration, System Architecture, Apis, Python, Enterprise solution design, AI platforms, AI solution delivery, Data pipelines, AI technologies

Understanding of cloud infrastructure and microservices, Familiarity with data governance and security compliance, Knowledge of customer journey mapping and omnichannel CX processes, CX orchestration and workflow design, Conversational AI or Agent Assist implementation, Data and integration expertise, Experience with reporting and analytics tools

Machine Learning, Security and Compliance for AI Solutions, Intelligent Automation, AI Solution Architecture, GenAI LLM applications, Data Engineering Fundamentals

Machine Learning, security and compliance for AI solutions, AI solution architecture, GenAI LLM applications, intelligent automation, data engineering fundamentals

Apis, Machine learning concepts, Advanced prompt engineering, Google Gemini, Data Analysis, Architectural design patterns, Generative AI models

MLops, Design Patterns, Python, Generative AI solutions, multi-agent workflows, Agentic systems, AI Tools

data engineering , Artificial Intelligence, Python, Sql, Pyspark, Devops, Api Integration, Microservices, Terraform, Azure Devops, Github, Kubernetes, Docker, Solution Architecture, Effort Estimation, Rfp, Rfi, Requirement Gathering, Solution Design, Cloud Architecture, Aws, Azure, Gcp, Data Architecture, Databricks, Etl, Resource Planning, Proposal Development, Stakeholder Management, Llm

Memory Management, Python, Enterprise AI governance, AI evaluation methodologies, Prompt engineering, Autonomous AI workflows, Hallucination mitigation, Tool orchestration, Responsible AI principles, Planning strategies, Response validation, Grounding techniques

Python, Pytorch, nemo, Deep Learning toolkits, nims, RAPIDS, Omniverse