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Lead the architecture and development of large-scale RAG and NLP systems for vertical AI platforms, using PyTorch, vector databases, and probabilistic modeling to deliver predictive intelligence for high-stakes industries.
Build and optimize LLM-powered AI agents that surface competitive intelligence for revenue teams, focusing on retrieval pipelines, orchestration, and evaluation to improve speed and accuracy.
Build and optimize LLM-powered backend systems for scalable AI-driven search and agentic workflows, focusing on retrieval pipelines, orchestration, and evaluation.
Build and deploy Generative AI systems for financial applications, including RAG pipelines, vector databases, and AI agents, using Python, AWS Bedrock, and LangGraph.
Build and deploy AI/ML pipelines using Python, FastAPI, and cloud services like GCP to serve vector-based models and microservices.
Builds and integrates Python-based AI services using LLMs, RAG pipelines, and vector databases for enterprise clients.
Builds and integrates Python-based AI services using LLM frameworks (LangChain, LangGraph), RAG pipelines, and vector databases for enterprise clients.
Build and optimize AI-driven automation workflows using Python, n8n, and OpenAI models, integrating systems with PostgreSQL and APIs.
Builds Python-based GenAI services using LLMs, LangChain/LangGraph, and vector databases for clients, integrating APIs and deploying with Docker.
Build and optimize AI-driven automation workflows using Python, JavaScript, and tools like n8n or Zapier, integrating models and APIs for enterprise clients.
Build and run the production infrastructure for Ingersoll Rand’s GenAI program, automating CI/CD, observability, and reliability for LLM-powered apps on GCP and Snowflake.
Build and operate the cloud and DevOps infrastructure that powers Ingersoll Rand’s GenAI program, focusing on GCP, Snowflake, CI/CD, and observability for LLM-based applications.
Build and operate the cloud and MLOps infrastructure that powers Ingersoll Rand’s GenAI program, focusing on GCP, Snowflake, CI/CD, and AI observability.
Build and tune LLM-based AI agents and RAG systems for ERP automation and SaaS knowledge bases, using Python, PyTorch, LangChain, and cloud pipelines.
Build LLM-based agents and RAG systems for autonomous network operations, integrating fault diagnosis, predictive analytics, and closed-loop decision support using Python, LangChain, and vector/graph databases.
Build and deploy enterprise Generative AI apps using LLMs, RAG pipelines, and AI agents with Python, LangChain, and vector databases.
Surf AI is the agentic operations platform for enterprise security teams. We don't just surface risk, we close it. Our platform connects context across identity, cloud, HR, IT, and SaaS systems, and uses…
Design and build scalable AI/ML infrastructure for a global fintech leader, focusing on real-time fraud detection and liquidity optimization using AWS, Kubernetes, and PyTorch.
Lead a team building and deploying enterprise data platforms, AI models, and generative AI solutions using Databricks, cloud-native tech, and AI tools like LangChain and Pinecone.
Build and maintain AI agentic backend systems using Python, LangChain/LangGraph, and vector databases to power autonomous workflows and RAG pipelines for business intelligence.
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