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Design and advise customers on generative AI and ML solutions using AWS services like Bedrock, SageMaker, and Nova, including RAG pipelines, agentic workflows, and model customization.
Build and integrate AI-enabled workflows, APIs, and cloud-native solutions to automate partnering operations and decision-making in Roche’s healthcare ecosystem using Python, AWS, and MLOps practices.
Build and deploy production-ready AI and multi-agent systems for healthcare, focusing on secure, compliant generative AI workflows using LLMs, RAG pipelines, and cloud platforms.
Build and scale Visa’s Java-based payment systems, integrating GenAI tools and LLM APIs to enhance backend services and developer workflows.
Build and improve Python-based backend services for AI-driven products, using Django/FastAPI, REST APIs, and databases, while collaborating in an agile team.
Lead a team building enterprise-grade AI/ML solutions for financial data operations, including LLMs, RAG, and multimodal models, while driving MLOps/LLMOps and cloud deployments.
Builds and maintains Snowflake-based data pipelines and models, using dbt, Kafka, and Python to deliver scalable, high-quality datasets for analytics and AI initiatives in a travel-focused loyalty/engagement platform.
Design and deliver enterprise-grade AI systems using LLMs, RAG, agentic workflows, and cloud-native platforms while ensuring security, compliance, and scalability for Nordic customers.
Builds backend systems in Java/Python to integrate AI/ML models (LLMs, embeddings) into scalable, production-ready agentic AI workflows for ING’s digital platforms, ensuring reliability, security, and observability while collaborating with data scientists and product teams.
Build and maintain AI platforms on AWS for AstraZeneca’s scientists, integrating vendor tools like Databricks and Domino and automating cloud-native deployments with Terraform and CI/CD.
Build and deploy autonomous agentic AI systems using RAG pipelines, vector databases, and multi-agent architectures on GCP to automate workflows and replace manual processes.
Build and deploy scalable AI/LLM solutions for Johnson Controls, focusing on generative AI, retrieval-augmented generation, and cloud-based ML pipelines to drive digital transformation.
Leads a tiger team to modernize AI/ML platforms, integrating LLMs (RAG, embeddings) and automating data pipelines for customer identity resolution, while mentoring teams on next-gen AI development and .NET/React-based infrastructure.
Lead the architecture and engineering of Citi’s global data and reporting platform, integrating federated query engines, BI tools, and AI-enabled interfaces while driving platform rationalization and adoption of generative AI tools.
Designs enterprise AI solutions on Microsoft’s stack, setting standards and guiding teams to build secure, scalable GenAI apps using Azure AI, Copilot Studio, and modern frameworks.
Build and optimize AI-ready data pipelines, vector stores, and retrieval systems using Airflow, Elasticsearch, and Python to power large-scale AI models and RAG applications.
Build secure, scalable AI-powered search systems using LLMs, RAG pipelines, and Elasticsearch for a government customer in a TS/SCI environment.
Lead a team building geospatial and AI-powered telecom software using ArcGIS, React, Python, and Azure, optimizing network planning and asset management for AT&T.
Design and operate AI-focused data pipelines that ingest, store, and process high-volume data for model-ready datasets, vector stores, and low-latency retrieval in a government defense context.
Build secure, scalable AI-powered search systems using LLMs, RAG pipelines, and Elasticsearch for a government customer in Chantilly, VA.
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