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 deploy multi-agent AI systems using LLM APIs (Bedrock, OpenAI, Mistral), LangGraph/LangChain, and AWS serverless tools; focus on execution, not design.
Build production-grade AI features like RAG pipelines and agentic workflows using Python, FastAPI, and vector stores; ship LLM-powered services end-to-end.
Build and deploy multi-agent AI systems using LLM APIs, agent frameworks, and AWS services, focusing on execution and integration rather than design.
Build and ship AI-powered agentic applications using Python, LangChain/LangGraph, and vector databases; lead system design, DevOps, and team mentorship.
Build and deploy production-grade agentic AI systems using Python/Java and React, orchestrating multi-agent workflows and retrieval pipelines while ensuring reliability and observability.
Design and build scalable cloud data pipelines on GCP and AWS, integrating batch and real-time streams for analytics and AI use cases.
Build and ship AI-powered marketing and sales platforms using Next.js, Node.js, and AI agents with LangChain/CrewAI, deploying on AWS/GCP via Terraform and GitHub Actions.
Build and deploy AI-powered document processing systems using Python, NLP, OCR, and LLMOps in a production Kubernetes environment.
Build and deploy generative AI agents, RAG systems, and ML models end-to-end using Python, LangChain, and Azure OpenAI to drive healthcare analytics and business impact.
Build and deploy agentic AI systems and LLM-powered applications for a global insurer, focusing on RAG, multi-agent orchestration, and robust MLOps pipelines.
Builds AI agents and RAG systems to automate marketing workflows, integrate APIs via MCP, and deliver generative insights for ad-tech and media clients.
Build autonomous AI agents and RAG systems to automate marketing workflows, integrating LLMs, vector databases, and cloud platforms like GCP/AWS.
Build and deploy production-grade LLM-based applications using Python/Java/TypeScript, integrating with OpenAI, Claude, and open-source models while optimizing cost, latency, and security.
Build and lead cloud-native data pipelines for regulatory reporting in investment banking, migrating legacy systems to AWS and integrating AI-driven workflows using Python, Kafka, and Kubernetes.
Design and implement AI-driven process reinvention solutions for clients using frameworks like crewAI and LangGraph, integrating data pipelines and process automation tools.
Build and evolve Roche’s internal AI Agentic Platform, designing scalable agentic workflows, reusable components, and enterprise integrations for secure, compliant AI solutions in healthcare.
Build and ship AI-powered web apps and agents using LLMs, Python/Node.js, and cloud tools; integrate AI into marketing platforms and internal tools for measurable business impact.
Principal engineer defining and building next-gen AI agent platforms on Oracle Cloud Infrastructure, leading multi-team execution and hands-on design of scalable, secure, and cost-aware agentic systems.
Build and scale production LLM-powered healthcare applications, including RAG pipelines, agentic systems, and evaluation frameworks, while ensuring compliance and reliability in a regulated environment.
Design and run the AI platform infrastructure that powers EY’s GenAI and agentic AI solutions, including deployment pipelines, observability, and governance at enterprise scale.
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