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Design and deliver Generative AI and AI-enabled solutions for workplace financial tools, using LLMs, RAG, vector databases, and APIs to automate workflows and integrate data.
Build and deploy AI solutions for Amgen’s drug discovery and operations, integrating GenAI, RAG, agents, and MLOps in a regulated healthcare environment.
Build and deploy AI/ML solutions end-to-end for Amgen’s AI Studio, turning business problems into scalable GenAI, RAG, and agent-based products with MLOps and enterprise integrations.
Build and own end-to-end AI products from problem framing to production deployment, focusing on GenAI, RAG, agents, and MLOps for Amgen’s healthcare domain.
Build and own production ML/AI components for Amgen’s AI Studio, including GenAI, RAG, and retrieval systems, using Python, SQL, and cloud services.
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.
Build and maintain the AI infrastructure for Scout’s electric vehicles, deploying LLM and ML services with Docker, Kubernetes, and Terraform across cloud and on-prem environments.
Designs and deploys production-grade generative AI systems on Databricks for enterprise clients, focusing on RAG pipelines, LLM orchestration, and vector search while leading technical delivery.
Lead AI platform strategy and roadmap for a fintech company, defining user-centric generative and predictive AI features while collaborating with engineering and business teams.
Build and scale secure AWS infrastructure (EKS, Lambda, Terraform) for AI/ML workloads, automate CI/CD with GitLab, and run a centralized observability stack (Prometheus/Grafana) to support production LLM inference and vector databases.
Build and deploy ML models, LLMs, and RAG systems for enterprise clients while learning consulting and cloud deployment under expert guidance.
Lead a team to design and industrialize scalable data platforms and AI solutions for large clients, from architecture to MLOps/LLMOps and agentic workflows.
Lead a team to design and deploy modern data architectures, MLOps pipelines, and GenAI solutions for enterprise clients, while managing projects and driving commercial growth.
Builds and deploys AI-powered solutions (LLMs, RAG, agentic systems) for insurance underwriting, operations, and customer workflows, focusing on production-grade integration, security, and observability in a regulated environment.
Lead a team of ML engineers and architects at an AI-first cloud services company, owning hiring, team growth, and complex customer engagements while shaping AI/ML architectures and driving pre-sales.
Leadership and Delivery Lead project delivery end to end, with clear governance, stakeholder communication, and accountability for outcomes Build and mentor a high-performing AI engineering team, establishing technical…
Build and deploy AI-powered agents and workflows using LLMs, RAG, and agentic frameworks to modernize enterprise software and drive scalable AI solutions.
Design and run AI/non-functional tests for an AI-powered construction estimating platform, including LLM evals, performance suites, and shift-left quality gates.
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