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Lead AI/ML product development for an insurance-focused platform, owning ML features that automate renewals and drive data-driven insights for brokerages.
Lead the design and delivery of responsible agentic AI systems for a digital bank, embedding fairness, safety, and regulatory compliance into production LLM-powered applications and platforms.
Design and build AI-driven backend services and RESTful APIs in Python for a Canadian bank, leveraging LLMs, RAG, and cloud-native architectures.
Principal AI/ML Architect designs and advises on production ML systems, MLOps/LLMOps pipelines, and GenAI architectures on AWS for enterprise clients, translating technical depth into business value.
Build and maintain Tangerine’s AI/ML platform, including MLOps, RAG pipelines, and agentic systems, to power next-gen banking features and client experiences.
Build and deploy AI agents and GenAI systems on AWS, integrating them into insurance workflows while optimizing performance and mentoring junior developers.
Build and run a production-grade agentic platform on Kubernetes using Go and Python, integrating AI agents with enterprise tools, memory, and security layers.
Principal AI Engineer at Mastercard designing and building enterprise-scale AI platforms, cloud-native systems, and GenAI solutions to power secure, reliable AI applications across the company.
Lead Benevity’s AI/ML strategy, designing scalable GenAI systems, LLM-powered features, and MLOps pipelines to deliver measurable business value from model training to production monitoring.
Lead the design and architecture of Stripe’s ML Platform, building scalable systems for training, serving, and monitoring ML models that power fintech products like Payments and Radar.
Lead a small team to design, build, and deploy production-grade generative AI systems using Python, RAG pipelines, vector databases, and cloud platforms while mentoring engineers and aligning solutions with business goals.
Build and lead Gen AI products using Python, React, and AWS, designing LLM pipelines, Agentic AI, and RAG systems while collaborating with cross-functional teams.
Build and deploy generative-AI models (RAG, zero/few-shot learning) for capital-markets use cases like summarization and conversational AI, integrating them into existing tools for research, banking, sales, and trading.
Build an AI-powered reliability assistant using LLMs, vector search, and RAG to help engineers resolve incidents faster by retrieving and synthesizing data from observability tools and past incidents.
Lead the design and deployment of AI/ML features for a commercial real estate SaaS platform, including LLM-powered tools and custom domain models, while setting engineering standards and mentoring teams.
Build and deploy production-grade AI systems for banks and insurers, automating back-office workflows with Python, ML frameworks, and compliance-first design.
Build AI-powered full-stack apps for Capital Markets clients using Python, FastAPI, React, and GenAI tools like RAG and LLMs.
Design and build secure, compliant AI/ML platforms on AWS and Azure for a large bank, including MLOps pipelines, guardrails, and observability for regulated environments.
Build and ship agentic LLM systems, RAG pipelines, and evaluation frameworks to power grant discovery and fundraising automation for nonprofits.
Design and build GenAI and agentic AI solutions—like conversational AI and RAG systems—on Databricks and AWS to improve wealth-management workflows and decision-making.
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