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.
AI Data Engineer (Data & Analytics) Data and Analytics at COMPLY: COMPLY is the worlds leading aggregator of financial and regulatory data to support compliance. Our mission is to help financial institutions meet…
Build and own AI/LLM systems for corporate spending management, including RAG, agent orchestration, and security controls, using Python and cloud-native tools.
Build and own Qashio’s AI/LLM platform, designing secure, vendor-neutral systems for agent orchestration, RAG, and compliance controls from prototype to production.
Build and deploy AI agents using LLMs (OpenAI, Claude, Gemini) and frameworks like LangChain to automate workflows and enhance fintech operations.
Build and deploy enterprise-grade AI solutions, including GenAI agents and RAG systems, using Python, cloud platforms (Azure/AWS), and frameworks like LangChain to improve customer experience and operational efficiency in an insurtech company.
Builds and deploys production AI systems like voice hardware, conversational agents, and RAG pipelines using Python, FastAPI, and ML frameworks.
Build, deploy, and monitor ML/AI models and GenAI systems using Python, TensorFlow, PyTorch, and MLOps tooling like MLflow and Kubernetes.
Designs and deploys LLM-powered agents and copilots, builds RAG pipelines, and integrates vector databases for client workflows.
Build and own AI/LLM systems for a fintech expense platform, designing secure RAG, agent orchestration, and evaluation pipelines in Python.
Builds and scales APIs, databases, and AI integrations for an AI-powered interview platform using Python, FastAPI, and PostgreSQL.
Builds and scales cloud-native backend services in Python/Node.js, using microservices, Docker, Kubernetes, and Azure, with a focus on security and performance.
Build and ship LLM-powered features for enterprise clients, including RAG systems, AI agents, and vector-based retrieval pipelines using Python, LangChain, and cloud tools.
Build and optimize GenAI systems using LLMs, prompt engineering, RAG, and agent workflows with frameworks like LangChain. Integrate APIs, vector databases, and external tools for scalable AI solutions.
Build and scale AI agents and ML pipelines using Python, PyTorch/TensorFlow, and frameworks like LangChain; integrate LLMs, vector DBs, and cloud-native systems.
Build AI-powered apps using Anthropic’s Claude API, integrating LLM workflows, prompt design, and tool use into scalable full-stack systems with React, Next.js, Node.js/Python, and vector databases.
Build full-stack web apps with React/Next.js and Node.js/PHP, integrating Anthropic’s Claude API to create AI-powered features like agents, RAG, and streaming responses.
Build and deploy multi-agent AI systems using LLM APIs (Bedrock, OpenAI, Mistral), LangGraph/LangChain, and AWS serverless tools; focus on execution, not design.
Build and deploy LLM/NLP models using Hugging Face, LangChain, and cloud AI services; implement RAG pipelines and vector search for AI-driven chatbots and Q&A systems.
Build production-grade AI features like RAG pipelines and agentic workflows using Python, FastAPI, and vector stores; ship LLM-powered services end-to-end.
Design and deploy AI/ML models, including LLMs and GenAI, to solve healthcare data challenges using Python, cloud platforms, and MLOps.
We couldn't check your fit for this role — add a CV to your profile to see it next time.