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Design, build, and operationalize LLM-powered applications, RAG systems, and intelligent agents for automotive industry use cases, spanning full-stack development from prototype to production using Python, React, cloud AI platforms, and vector databases.
Builds and scales GenAI full-stack applications (RAG, intelligent agents) for clients, bridging backend (microservices) and frontend (React) while managing cloud infrastructure, CI/CD, and LLM monitoring.
Life at UiPath The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make…
Architects AI-powered GTM systems by defining low-code and custom agentic workflows (LangGraph, LangChain) for automation, integrating Salesforce/NetSuite, and setting enterprise-grade design standards for GTM engineering teams.
Designs and deploys advanced AI/ML systems (LLMs, agentic workflows, multimodal models) for government/commercial clients, optimizing for production, edge, and security.
Principal Architect performing consultative discovery with clients to translate business goals into enterprise architectures, driving adoption of AI services (including agentic AI workflows) and cloud migration. Core technologies include AWS (Bedrock, Amazon Q), generative AI platforms (Claude, ChatGPT, Gemini), and agentic frameworks (LangGraph, CrewAI).
Builds AI-driven automation workflows using GenAI/Agentic tech to streamline fintech processes like onboarding, transactions, and reporting; integrates LLMs and RAG for context-aware decision support.
Build and maintain Geotab’s internal AI and generative-AI platform, enabling data scientists to train models, access LLMs, and deploy agent applications at scale using Python, cloud services, and container orchestration.
Build and maintain Geotab’s internal AI/ML and generative-AI platform, enabling data scientists to train models, access LLMs, and deploy GenAI agents at scale.
Designs and builds scalable, secure AI/ML platforms for healthcare, focusing on agentic systems, RAG pipelines, and multi-modal AI applications with guardrails and observability. Leads architectural standards, cloud-native infrastructure (Azure/AWS), and AI governance for enterprise-grade solutions.
Designs, builds, and deploys AI agents and automation pipelines to supercharge business workflows in domains like sales, operations, and customer experience, using LLMs, APIs, and cloud tools.
Build and deploy generative AI and ML solutions for federal clients, from RAG pipelines to agentic workflows, while standardizing reusable recipes and best practices for Snorkel’s tooling.
Build and maintain ETL/ELT pipelines, data models, and AI-ready datasets for an insurance tech platform using cloud data tools and Python/SQL.
Builds and deploys production-grade agentic AI systems (Python/React) for enterprise clients, focusing on agent workflows, RAG pipelines, and MCP integrations while maintaining DevOps/AgentOps practices.
Deploys and integrates Google’s generative AI systems (e.g., Gemini, Vertex AI) into enterprise environments, resolving integration/data/state issues to ensure production-grade AI workflows. Bridges customer needs with Google Cloud’s product roadmap via field insights and best-practice collaboration.
A forward-deployed engineer building scalable, multi-tenant Java/Spring Boot microservices on Azure, integrating LLM-based AI capabilities (RAG, agents) via frameworks like LangGraph, CrewAI, and Semantic Kernel.
The Lead AI/ML Engineer will build an Agentic AI platform for site reliability and incident automation at RBC. The role involves designing autonomous agents using LangChain and LangGraph to optimize system resilience and monitoring within a financial services environment.
Embedded AI engineer at Google Cloud who builds, deploys, and optimizes bespoke agentic AI solutions for high-value public sector clients, bridging Google’s AI products with customer infrastructure while driving product roadmap improvements.
Designing and deploying Agentic AI and Generative AI solutions using LangChain, LangGraph, RAG architectures, and LLM orchestration frameworks in London.
The AWS AI Agent Engineer will design, build, and operate enterprise-grade AI agents and multi-agent workflows using Amazon Bedrock and AWS serverless technologies. The role focuses on implementing RAG, orchestration, and observability to ensure reliable, secure, and cost-effective production AI applications.
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