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Builds Flask web apps and Plotly Dash dashboards for banking analytics, integrates local LLMs and RAG pipelines, and automates risk/compliance workflows.
Build and deploy generative AI apps using Python and LangChain, focusing on RAG systems, LLM orchestration, and vector databases.
Design and build enterprise-grade AI systems using RAG, agentic workflows, and cloud platforms for HR and finance domains.
Build and deploy generative AI agents, RAG systems, and ML models end-to-end using Python, LangChain, and Azure OpenAI to drive healthcare analytics and business impact.
Design and implement end-to-end AI solutions using Python, PySpark, Databricks, Postgres and open-source LLMs like Qwen, building data pipelines, RAG systems and AI agents for enterprise clients.
Build and maintain data pipelines, clean and structure financial data, and integrate GenAI solutions like LLMs and RAG for a banking-focused project using Python, SQL, and ETL/ELT.
Builds AI agents and RAG systems to automate marketing workflows, integrate APIs via MCP, and deliver generative insights for ad-tech and media clients.
Build autonomous AI agents and RAG systems to automate marketing workflows, integrating LLMs, vector databases, and cloud platforms like GCP/AWS.
Build and scale Evolve’s proprietary education platforms from the ground up, covering full-stack development, cloud deployment, and database design for internal and external use.
Build and deploy production-grade LLM-based applications using Python/Java/TypeScript, integrating with OpenAI, Claude, and open-source models while optimizing cost, latency, and security.
Design and scale real-time data pipelines for AI systems, focusing on RAG, vector databases, and semantic layers to power agentic reasoning in enterprise environments.
Build real-time data pipelines and vector databases to power AI agents, transforming enterprise logs into embeddings for RAG systems with automated quality guardrails.
Build and maintain scalable data pipelines and cloud data platforms for banking clients, using Spark, Scala, and cloud services to deliver clean, governed data for analytics and AI.
Build LLM-powered automations, chat/voice assistants, and RAG pipelines using Python, FastAPI, and vector databases; deploy cloud-native services with CI/CD and guardrails.
Build and ship AI-powered web apps and agents using LLMs, Python/Node.js, and cloud tools; integrate AI into marketing platforms and internal tools for measurable business impact.
Build and secure data pipelines for a banking client, using Scala, Spark, and cloud platforms to process large-scale data into reliable, business-ready datasets.
Build and deploy RAG pipelines and large-scale AI systems for industrial use cases like predictive maintenance and smart factories using Python, PyTorch, and vector databases.
Build and scale AI/ML pipelines and GenAI systems for GE HealthCare, automating model deployment, monitoring, and lifecycle management across hybrid/multi-cloud (AWS, Azure).
Build and scale production LLM-powered healthcare applications, including RAG pipelines, agentic systems, and evaluation frameworks, while ensuring compliance and reliability in a regulated environment.
Build and ship the AI backbone for a property-management assistant: RAG pipelines, multi-step agent workflows, and LLM integrations that power daily operations for 20,000+ HOA and condo communities.
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