Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Build and refine enterprise-grade AI agents for document processing and automation using NLP, prompt engineering, and RAG pipelines.
Build and deploy production-grade AI systems using RAG, agentic frameworks (LangGraph, AutoGen), and vector search (Azure AI Search, pgvector) with Python and cloud tools.
Build and optimize ML models, LLMs, and RAG systems using Python, TensorFlow, and PyTorch, and deploy them on cloud platforms like AWS or Azure.
Build and deploy multi-step AI agent workflows using LangChain, LlamaIndex, and platforms like Azure AI Studio Agents or AWS Bedrock Agents, integrating APIs and databases for automation.
L’IA chez Smile, ce n’est pas un buzzword : c’est une pratique. Des modèles et des cas d’usage ouverts, performants et durables, pensés pour passer en production — pas des PoC qui finissent au tiroir. On bâtit sur des…
Designs and builds generative AI systems using LLMs, agentic architectures, and RAG pipelines, then deploys and monitors them in production.
Build AI agents, RAG/vector search, and platform integrations to automate workflows and enhance ETP Hub with AI-enabled tools for document search, summarization, and task assistance.
Lead AI Engineer builds and deploys production LLM apps, designs reasoning agents, and integrates AI with cloud infrastructure and enterprise systems using Python and AWS.
Develops and maintains cloud-based AI agents and RAG pipelines on Azure, mentors engineers, and ensures production stability for healthcare diagnostic platforms.
Lead enterprise AI/ML and generative AI initiatives, designing and deploying LLM-based solutions, setting strategic roadmaps, and mentoring teams to drive scalable, secure AI adoption in a large financial services firm.
Lead the design and deployment of agentic AI systems for Citi’s banking operations, using Python, Google ADK, LangChain, and LLMs to automate workflows and reduce risk.
Build production-ready GenAI systems using Python, React, and AWS, including LLM pipelines, RAG, and agent-based architectures for scalable AI products.
Build and deploy AI solutions (ML, generative AI, agentic workflows) in Python, integrating with enterprise systems to solve business problems and move prototypes to production.
Principal AI/ML Architect designs and advises on production ML systems, MLOps/LLMOps pipelines, and GenAI architectures on AWS for enterprise clients, translating technical depth into business value.
Build and integrate GenAI features using OpenAI APIs to auto-generate audit-ready client summaries from structured data for financial-crime compliance, focusing on prompt engineering, backend integration, and responsible-AI guardrails.
Lead Benevity’s AI/ML strategy, designing scalable GenAI systems, LLM-powered features, and MLOps pipelines to deliver measurable business value from model training to production monitoring.
Build and lead Gen AI products using Python, React, and AWS, designing LLM pipelines, Agentic AI, and RAG systems while collaborating with cross-functional teams.
Build and ship agentic LLM systems, RAG pipelines, and evaluation frameworks to power grant discovery and fundraising automation for nonprofits.
Design and build GenAI and agentic AI solutions—like conversational AI and RAG systems—on Databricks and AWS to improve wealth-management workflows and decision-making.
Hello, we’re Instrumentl. Nonprofits do some of the most important work in the world, and most of them are still managing grants in spreadsheets. We’re fixing that. Instrumentl is a profitable, hypergrowth, YC-backed…
We couldn't check your fit for this role — add a CV to your profile to see it next time.