data engineering , Cloud Architecture, Databases, Microsoft Azure, Python, AWS, Oauth, Google Cloud Platform, Api Development, Distributed Systems, Model fine-tuning, JSON-RPC, Microservices architecture, GraphRAG, Generative AI, LLMOps, AI evaluation frameworks, MCP REST APIs, AI architecture, LoRA, SQL agents, QLoRA, Advanced retrieval architectures, Event-driven architectures

snowflake , MLops, Gcp, Databricks, Azure, AWS, Data engineering pipelines, Hyperscaler solutions, LLMOps, Palantir, Technical architecture design, AI ML Data Science, GenAI architectures

MLops, compliance alignment, agent workflow orchestration, evaluation dataset design, defining guardrails standards, LLMOps, AI GenAI architecture patterns, corpus preparation, prompt lifecycle management, CI CD, Security-by-design, network boundaries, monitoring approach, Data strategy architecture, embedding design, retrieval strategy, Governance guardrails, model registry, deployment strategy, Access Control, solution reference architectures

Python Programming, Microsoft Azure cloud platform, Agile-based principles and tools

Tensorflow, Nlp, Pytorch, Python, Matching reconciliation algorithms, LLM-based systems, Classification, Entity extraction, Production AI deployment, ML frameworks

Gcp, Node.js, FastAPI, Jira, Azure, Python, AWS, Generative AI, AI Governance, Multi-cloud AI platform architecture

Python, Agentic AI, Multi-Agent Systems, Generative AI, LLMs, Prompt Engineering, Reasoning Frameworks, RAG, Retrieval-Augmented Generation

Databricks, Azure, Vector Databases, Azure AI Agents, evaluation tools, OpenAI, Microsoft Agentic Framework, Gen AI LLMs