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 LLM-based AI pipelines and services, integrating them into corporate products and systems using Python, RAG, and vector databases.
Design and implement AI security controls, threat detection, and incident response for Absa’s AI/ML systems, including LLMs, agentic AI, and MCP ecosystems, while hunting for adversarial threats.
Build and deploy agentic AI systems and LLM features like RAG with citation, handling end-to-end AI/ML projects from data prep to deployment.
Build and scale an AI-powered clinical reasoning system that handles millions of patient consultations, improving safety and accuracy through agentic architectures, retrieval, and continuous learning.
Lead the design and deployment of production-grade AI systems, including LLMs, RAG, and agentic AI, using FastAPI/Flask and MLOps pipelines.
Build and deploy AI-powered expert systems for legal, tax, and compliance using RAG, custom agents, and MLOps/LLMOps pipelines in Python and cloud environments.
Oversee independent security validation for an organization’s AI/LLM ecosystem, conducting adversarial testing and control assessments to ensure models, APIs, and infrastructure are secure and compliant before deployment.
The Manager: AI Architecture is responsible for designing, governing, and evolving the organization’s end-to-end Artificial Intelligence (AI) architecture. The role ensures AI solutions are scalable, secure, ethical,…
Design, fine-tune, and deploy large language models for healthcare applications, build RAG pipelines, and curate training data.
Leads independent security assurance for an organization’s AI/LLM ecosystem, conducting adversarial testing, validating controls, and ensuring AI solutions are secure, compliant, and production-ready.
Get to Know Our Team The Fulfilment Engineering team builds the technology that connects demand with supply across Grab’s services. We solve complex marketplace problems spanning allocation, driver experience,…
Builds RAG workflows and AI-agent pipelines using Teradata-Claude integrations in Python/SQL, optimizing data models and ETL/ELT for advanced analytics.
Designs and refines prompts for LLMs like ChatGPT and Azure OpenAI to power AI apps, automations, and chatbots that improve productivity and user experiences.
Senior AI Engineer builds and deploys production-grade ML and LLM systems, turning business needs into scalable AI pipelines and models using Python and SQL.
Build and deploy LLM-powered agentic systems that autonomously perform structured tasks, integrating AI into existing software with a focus on reliability and scalability.
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.
Design and build autonomous AI agents that decompose goals into actionable steps, integrate with enterprise systems, and deploy robust, observable agentic workflows with built-in failure handling.
Build autonomous AI agents and data pipelines using LangChain/LangGraph or Google Vertex AI Agent Builder to automate analytics and decision-making at scale.
Senior AI Engineer designs and deploys enterprise AI systems using TensorFlow, PyTorch, and LLM APIs, building scalable ML pipelines and computer vision/NLP solutions for fintech and healthcare clients.
We couldn't check your fit for this role — add a CV to your profile to see it next time.