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.
Lead AI engineering for generative-AI copilots and RAG systems in a regulated financial-services environment, building production-grade Python/LLM pipelines on Azure.
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.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases. Develop agents, prompts, and integrations with clean code and CI/CD in Python, Java, or TypeScript.
Custom Software Engineer at Accenture in Chennai builds agentic AI applications using LLM tooling, RAG pipelines, vector search, and API integrations, with core techs including Java Full Stack, Python, TypeScript/Node.js, and vector DBs.
Build agentic AI applications using LLMs, RAG pipelines, and vector search, integrating enterprise APIs and data sources into production systems.
Build AI-powered applications using LLMs, RAG pipelines, and vector search, integrating APIs and enterprise systems while owning full-stack development from prototype to production.
Build AI-powered agentic applications by implementing LLM tooling, RAG pipelines, and vector search; integrate with enterprise systems while ensuring scalability, safety, and rapid iteration.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector search, integrating enterprise APIs and ensuring robust, testable code and CI/CD.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and evaluation loops while integrating enterprise APIs and ensuring robust CI/CD.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and evaluation loops with Python/TypeScript/Java.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; develop scalable agentic systems with Python/TypeScript/Java and modern frameworks.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating APIs and cloud services while owning end-to-end development and testing.
Builds AI-powered agentic applications (LLM tooling, RAG pipelines, vector search) from prototype to production, integrating with enterprise systems while ensuring scalability, safety, and observability.
Build AI-powered applications using LLMs, RAG pipelines, and vector search; implement agents, prompts, and evaluation loops with Python/TypeScript/Java and modern frameworks.
We couldn't check your fit for this role — add a CV to your profile to see it next time.