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Lead Security Engineer at JPMorgan Chase designs and implements tamper-proof security solutions for enterprise software, leveraging Java/Python, AI/ML (PyTorch/TensorFlow), GenAI (LLMs, RAG), and threat modeling to harden systems against misuse and vulnerabilities in financial services infrastructure.
Principal Architect leading HR technology, workforce data, and AI solutions at Westpac, designing enterprise-scale People platforms and driving modernization in a regulated banking environment.
Build and deploy AI/Generative AI solutions using LLMs, RAG, and cloud platforms to drive insights and automation for Mastercard’s global operations.
Build and deploy generative-AI solutions using LLMs, prompt engineering, fine-tuning, embeddings, and RAG pipelines for enterprise use cases like customer service and document automation.
Build and deploy generative AI systems using RAG, LLMs, and cloud-native MLOps on Azure, while mentoring teams to deliver scalable AI solutions across industries.
Build and deploy enterprise-scale AI systems (RAG, agentic workflows, LLMs) to automate workflows and improve resilience for a global financial markets infrastructure provider.
Design and deploy enterprise-scale AI/ML solutions, including deep learning and generative models, with MLOps/LLMOps pipelines and cloud integration.
Build and deploy production-grade ML models for retail, pricing, and operations analytics using Python, SQL, and Azure ML.
Fine-tunes and adapts large language models for domain-specific use cases using Python, AWS, and MLOps pipelines to improve accuracy and contextual relevance.
Build and deploy AI systems for Fortune 100 clients, designing scalable architectures and troubleshooting production issues while bridging engineering and customer needs.
Forward-deployed engineer partners with Fortune 100s to design, deploy, and troubleshoot production AI systems and integrations.
Design and enforce AI security controls for an AI-first enterprise platform, including agent governance, model risk management, and ML-driven threat detection across 500+ customer environments.
Build and automate scalable ML pipelines on Azure and Databricks, containerize models with AKS, and ensure resilient, cost-optimized deployments for healthcare products.
Build and improve demand-forecasting models using Python and SQL, collaborating with engineers and business teams to deploy multivariate algorithms and enhance supply-chain decisions.
As an Engineering Manager, AI & ML (Data Collection), you will play a critical role in building and scaling the company’s Unified AI/ML Data Collection Platform , enabling standardized, reliable, and scalable…
Build and deploy ML models (XGBoost, NLP, deep learning) in AWS to solve client problems, using PySpark, SQL, and MLOps pipelines.
Lead AI/ML and cloud transformation for global healthcare clients, defining enterprise architectures and guiding executives on responsible AI adoption and AWS best practices.
Designs and delivers scalable cloud, data, and AI solutions for life insurance, leveraging Azure AI, Databricks, and modern architectures while ensuring compliance and business alignment.
Lead architect guiding healthcare software teams to modernize legacy systems with cloud and AI, designing scalable AWS-based solutions for post-acute care workflows.
Lead AI/ML projects for enterprise clients, designing and deploying custom deep learning and generative AI models with MLOps/LLMOps pipelines in cloud environments.
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