Design Patterns, Software Development Lifecycle, Testing, Coding Standards, Generative AI, Code reviews, Build processes, Livesite operations, Certification, Reliability and scaling, Source control management, Large-scale distributed systems, Agentic workflows

Databases, Java, CSS, HTML, Javascript, Application Servers, Restful Apis, middleware, Generative AI, LLMs, AI Agents, Agentic Workflows, Infrastructure, RAG, MCP

Information Retrieval, measurement systems, semantic retrieval ranking models, generative AI product experiences, search relevance ranking, data fluency, Competitive Benchmarking, query understanding

data engineering , Power Bi, Data Science, Data Governance, Sql, Devops, Test automation, MLops, Spark, Agile, Databricks, Scrum, Azure, Python, Generative AI frameworks, Cloud-native development, Data platform architectures, CI CD, Analytics, AI ML pipelines, Model lifecycle management

product discovery , Requirements Management, Release planning, Agile Software Development, AI-assisted product discovery and documentation tools, Microsoft Azure fundamentals, Product lifecycle management, Product roadmap planning

Technical background in software engineering data or AI, Experience delivering Generative AI LLM projects, Experience with AWS Azure or Google Cloud, Good understanding of AI ML concepts GenAI LLMs APIs and cloud technologies, Experience with project management tools such as Jira Confluence Azure DevOps or similar, PMP PMI-ACP Scrum Master or equivalent certification, AI GenAI project experience