Shoaib User
@shoaibuser1
Lead Generative AI Architect driving enterprise LLM/ML Ops and scalable AI platforms.
What I'm looking for
I am a Lead Generative AI Architect with 10+ years of progressive experience driving digital transformation from foundational data science to strategic generative AI leadership. I design, build, and deploy enterprise-scale LLM and GenAI solutions—including RAG, fine-tuning, and agentic frameworks—across multi-cloud environments.
At Striveworks I architected and led multi-cloud LLM Ops for five+ GenAI solutions, integrated Gemini 2.0 via Discovery Engine, and implemented RAG systems using Pinecone and Weaviate to cut hallucination rates by over 50%. I drove technical vision for foundational AI systems and established enterprise LLM adoption and governance frameworks.
Previously, I reduced deployment cycles by 55% through automation of ML and data pipelines, optimized transformer NLP models for a 30% improvement in personalization, and engineered a real-time fraud detection engine deployed as FastAPI microservices. I champion Responsible AI practices, security, and compliance (HIPAA, GDPR, SOC2).
I mentor engineers on advanced techniques (distillation, quantization, A2A protocols), and I focus on scalable, production-grade MLOps/LLMOps—combining LangChain/LangGraph/LlamaIndex tooling, CI/CD, observability, and cloud-native deployment to deliver measurable business outcomes.
Experience
Work history, roles, and key accomplishments
Lead Generative AI Architect
Striveworks
Aug 2021 - Present (4 years 5 months)
Architected and led multi-cloud LLM/GenAI solutions (RAG, fine-tuning, agentic frameworks) integrating Gemini 2.0 and Azure AI Foundry, reducing hallucination rates by over 50% and increasing customer service automation by 5%. Established enterprise LLM adoption, governance, observability, and Responsible AI practices across teams.
Senior AI/ML Engineer
Omneky
Jun 2019 - Jul 2021 (2 years 1 month)
Automated ML and data pipelines across multi-cloud environments, reducing deployment cycles by 55% and improving personalized customer experiences by 30% via transformer-based NLP models. Engineered a real-time fraud detection pipeline deployed as FastAPI microservices, increasing fraud capture by 5%.
AI/ML Engineer
Petuum
Jan 2017 - May 2019 (2 years 4 months)
Built deep learning CNN models for a healthcare pilot that accelerated diagnostic review and achieved measurable accuracy improvements, and implemented ETL pipelines with PySpark and SQL, yielding a 22% reduction in operational costs through predictive models.
Data Scientist
Rapid Innovation
Aug 2015 - Jan 2017 (1 year 5 months)
Led end-to-end data cleansing, feature engineering, and statistical analysis to build segmentation and churn models that increased retention by 15% and improved analytic data pipelines and dashboards for stakeholders.
Education
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