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Build and scale Java-based microservices for global e-commerce platforms, integrating Agentic AI to automate development tasks and enhance supply chain systems.
Design and lead a scalable .NET-based AI platform for multilingual localization, integrating LLMs and microservices to process large volumes of text and audio data.
Build and deploy AI agents that automate workflows, integrate with enterprise systems, and deliver intuitive front-end interfaces for Shell’s energy and enterprise use cases.
Build and ship AI-powered features into existing C#/.NET products using Azure AI, RAG, and agentic workflows, taking ideas from proof-of-concept to production.
Lead AI integration at a global bank, building LLM-powered features and GenAI agents to enhance financial applications and user workflows.
Design and deploy AI agents that integrate with investment workflows to enhance research, portfolio construction, and risk analysis for an asset-management firm.
Designs and leads enterprise-scale .NET/Python architectures for PNC’s lending tech, focusing on cloud-native microservices, AI/ML integration (LLMs, agents), and modernizing legacy systems to improve operational efficiency and customer experience.
Build and own production ML/AI components for Amgen’s AI Studio, including GenAI, RAG, and retrieval systems, using Python, SQL, and cloud services.
Senior ML engineer building and scaling enterprise-grade AI/ML platforms, MLOps pipelines, and GenAI services for a global biotech company.
Build and deploy production ML and GenAI components—models, RAG systems, agents, and pipelines—using Python, SQL, and cloud services to power Amgen’s healthcare-focused AI products.
Senior ML engineer building and scaling enterprise-grade AI/ML and GenAI platforms, including MLOps pipelines, model services, and full-stack applications for Amgen’s healthcare data needs.
Build, deploy, and monitor ML models and MLOps pipelines on AWS for forecasting and GenAI apps in a biotech setting.
Designs and leads enterprise-scale .NET/Python architectures for PNC’s lending tech, focusing on cloud-native, AI-driven solutions, microservices, and event-driven systems to modernize legacy platforms and drive business growth.
Builds and deploys autonomous AI agents, multi-agent systems, and generative AI solutions using frameworks like LangChain, AutoGen, and Azure OpenAI to automate enterprise workflows, enhance decision-making, and deliver scalable AI-driven business value.
Advise and enable engineering teams on AI adoption, focusing on LLM integration, RAG pipelines, and agentic architectures while ensuring reliability, observability, and governance compliance in healthcare AI systems.
Build and operate the interface, semantic layer and controls that let AI agents safely interact with IFS enterprise software, focusing on MCP servers, knowledge graphs and agentic workflows.
Build AI-powered agentic workflows and RAG systems for enterprise clients using LLMs, agent frameworks, and retrieval pipelines, while leading technical aspects of consulting projects.
Build full-stack web apps and integrate AI features using modern stacks (React, Node.js, Python, Java/Spring Boot) and cloud platforms (AWS/Azure/GCP), while leveraging AI coding assistants daily.
Build and deploy AI-powered applications end-to-end, integrating LLMs, prompt engineering, and full-stack development to create next-generation AI systems for real-world business problems.
Build and maintain full-stack enterprise apps using React, FastAPI, Python, and AWS, integrating AI/ML features and DevOps practices for a biotech company.
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