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Build and deploy production-grade LLM applications and agentic workflows that turn unstructured text into business insights, using RAG, prompt engineering, and modern cloud data platforms.
Design and lead AI-powered test automation frameworks using LLMs, RAG, and agentic AI to enhance software quality and integrate intelligent testing into CI/CD pipelines.
Lead AI strategy and architecture for a Brazilian organization, designing scalable Generative AI solutions with Microsoft Azure AI tools, establishing MLOps/LLMOps practices, and guiding teams on LLMs, RAG, and AI agents.
Lead AI-native product initiatives to streamline clinical trial workflows using Generative and Agentic AI, shaping strategy from prototyping to scaled delivery.
Build and deploy GenAI-enabled solutions for government clients using Microsoft Azure AI tools, Python/TypeScript, and RAG workflows while collaborating with senior stakeholders to drive measurable business impact.
Leads a team building and operating an MLOps platform and multi-agent environment, overseeing the full ML lifecycle, AI agent integration, and scalable infrastructure for a large corporation.
Design autonomous network solutions for telecoms using AI frameworks (Vertex AI, LangGraph), APIs, and vector databases to optimize agentic systems and reduce inference costs.
Build and deploy cutting-edge forecasting models and LLM agents for scenario planning in banking, using PyTorch, LangChain, and production-grade MLOps tooling.
Build LLM-based agents and RAG systems for autonomous network operations, integrating fault diagnosis, predictive analytics, and closed-loop decision support using Python, LangChain, vector/graph databases, and Kubernetes.
Build and deploy AI systems, including LLM-based agents and retrieval workflows, using Python and cloud-native stacks to power healthcare products and enterprise solutions.
Designs enterprise-scale AI architectures for healthcare, including generative AI apps, agentic systems, and LLM-powered workflows, while ensuring security, compliance, and cloud-native integration.
Build end-to-end agentic AI workflows using React front-ends, C#/.NET orchestration, and Azure OpenAI, shipping resilient multi-agent systems with rigorous evaluations.
Build and optimize LLM-powered AI assistants for a bank’s internal support systems using Python, RAG, and vector databases.
Build and optimize LLM-powered AI assistants for a bank’s customer service channels, integrating models like GPT and Llama with internal APIs and RAG architectures.
Principal AI Engineer designs and builds a centralized AI platform and agentic frameworks for healthcare use cases, integrating clinical NLP, structured evidence graphs, and policy engines while ensuring regulatory compliance.
Lead the AI and data platform for a live-commerce marketplace, building pipelines, personalization, and automation systems that power buyer experiences, seller tools, and marketing campaigns using Python, ClickHouse, and LLMs.
Build and maintain enterprise-scale agentic AI platforms, integrations, and workflows using Python/Java/Go, LangChain, and GCP/Vertex AI.
Lead the design and development of enterprise AI solutions using Python, RAG, Agentic AI, and LLMs, while engineering enterprise data pipelines and integrating AI into production.
Builds autonomous AI agents and multi-agent systems using LangGraph/LangChain to automate workflows, integrating LLMs and APIs for real-world actions.
Build and deploy production-grade AI and GenAI solutions for banking products, using Python, TensorFlow/PyTorch, and cloud-native tooling.
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