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Builds full-stack web apps in Python (Flask/Django) with React/TypeScript front ends, integrating LLM capabilities via RAG and processing large datasets with PostgreSQL, ArangoDB, and vector search.
Key Responsibilities 1. Rapid Prototyping & Application Development Build AI applications, copilots, and agentic workflows end-to-end – UI, APIs, business logic, and model integration. Use rapid development tools…
Build and deploy enterprise-grade generative AI systems (LLMs, RAG, agents) for Citi’s operations, integrating models like GPT-5 and Claude into Python services and APIs.
Design and deploy production-ready AI systems, including LLM apps, RAG pipelines, and voice AI, for clients across healthcare, ecommerce, travel, and other sectors.
Build and deploy enterprise-grade AI systems, including LLM agents, retrieval pipelines, and AI gateways, using Python/TypeScript and modern AI engineering patterns.
Design and deploy autonomous AI agents using LLM/RAG to automate media planning, ad buying, and financial audits for an ad-tech client, covering the full lifecycle from modeling to production.
Build and deploy generative-AI solutions using LLMs, RAG, and AI agents in Python on AWS, integrating with enterprise systems for a U.S. client.
Gigi is the agentic operating system of enterprise media buying. Our first product is the AI media manager for Amazon DSP. Since launching it in summer 2025, we've grown to manage hundreds of millions in…
Builds and deploys LLM/NLP-based AI agents, RAG systems, and GenAI pipelines using Python, FastAPI, and PyTorch for enterprise clients.
Build and scale SentinelOne’s AI Gateway infrastructure (Kong-based) to route, secure, and monitor AI coding assistant traffic, while operating self-hosted LLM stacks and driving reliability across Kubernetes and CI/CD systems.
Build and scale SentinelOne’s AI Gateway infrastructure (Kong-based) to route, secure, and monitor AI coding assistant traffic, while operating self-hosted LLM stacks and driving reliability across Kubernetes and CI/CD tooling.
Build and scale backend services for Constructor’s AI-powered e-commerce search platform, focusing on ML infrastructure, model serving, and distributed systems.
Designs and implements AI/ML and generative AI solutions for enterprise clients, focusing on architecture, LLM/RAG pipelines, and MLOps—collaborating with data and product teams to scale AI from proof-of-concept to production while ensuring security, governance, and cloud platform integration.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, then integrate them into enterprise systems with clean, testable code and CI/CD.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases; implement tools, prompts, and CI/CD while integrating enterprise APIs and ensuring safety.
Builds AI-native applications by implementing LLM tooling, RAG pipelines, and vector search; integrates AI into enterprise systems with Python/TypeScript/Java, frameworks like LangChain, and vector DBs (pgvector, Pinecone).
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating enterprise APIs and ensuring robust testing and safety. Core stack includes Python, TypeScript/Node.js, and Java with frameworks like LangChain and Spring Boot.
Build agentic AI applications using LLMs, RAG pipelines, and vector search; implement tools, prompts, and CI/CD while integrating enterprise APIs and data sources.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases. Develop, test, and integrate agents with enterprise APIs and cloud services.
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