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.
Leads end-to-end AI solution design, development, and evolution, guiding engineering teams to build scalable, production-grade AI systems with GenAI, multi-agent frameworks, and cloud infrastructure.
Build and maintain cloud-native back-end services for maritime IT networks while integrating AI/LLM features like RAG pipelines and agentic workflows using Python and distributed systems.
Build and scale ML feature pipelines in Snowflake/Snowpark and Databricks, productionize batch/real-time inference, and implement MLOps/LLMOps to drive measurable business impact.
This role leads AI product strategy, roadmapping, and delivery for SharkNinja, defining AI initiatives that drive revenue growth or operational efficiencies while ensuring compliance and data integrity.
The AI Platform Engineer will design and operate enterprise AI/GenAI platforms, focusing on LLMOps, MLOps, and building reusable AI services like RAG and inference APIs. The role also involves developing CI/CD pipelines and coaching teams on DevOps best practices within a capital markets environment.
84.51° Overview: 84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable…
Senior AI engineer deploys and advises on cutting-edge GenAI solutions for U.S. federal clients, integrating Databricks AI research with production tools like LangChain and PyTorch.
Lead end-to-end GenAI and Agentic AI architecture, translating business requirements into scalable enterprise AI solutions using GenAI, ML, LLMOps, RAG, LangChain, .NET, and Azure.
Senior engineer builds autonomous AI agents and retrieval systems to modernize legacy software for federal healthcare, delivering explainable, traceable answers from decades of source code.
Lead the design and implementation of AI platforms and strategies, focusing on Generative AI, LLMs, RAG, and AI agents for enterprise solutions in a remote role.
Description Role Summary The AI Engineer will build and operationalize the tooling, pipelines, and controls that secure Ulta's growing portfolio of AI initiatives. This is a hands-on engineering role responsible…
About Starburst Starburst delivers enterprise intelligence at scale by giving organizations secure, governed access to all their data, wherever it lives. Built for distributed data environments, Starburst helps…
The Senior AI Engineer will design and implement evaluation pipelines, observability frameworks, and quality metrics for AI-powered features within a board intelligence platform. The role involves hands-on development in Python or C#/.NET to ensure LLM-based systems are reliable, cost-effective, and performant in production.
Overview With more than 45,000 employees and partners worldwide, the Customer Experience and Success (CE&S) organization is on a mission to empower customers to accelerate business value through differentiated…
Design and ship production LLM/GenAI agentic workflows for an AI-powered bid management SaaS platform, owning the full cycle from prototyping through evaluation, deployment, and observability on Azure using Python.
This role involves architecting and building autonomous AI agents and RAG pipelines to automate enterprise workflows for non-technical users. The engineer will work on the full stack of LLM orchestration, tool-use, and production deployment using technologies like Python, Spark, and various vector databases.
The AI Platform Engineer will build and maintain enterprise GenAI, LLM, and MLOps platforms, focusing on RAG services, CI/CD pipelines, and DevOps automation. This role is based in Halifax and requires a hybrid work schedule with four days in the office.
The AI Platform Engineer builds and operates enterprise GenAI and LLM platforms, focusing on MLOps frameworks, RAG, and CI/CD automation. The role requires expertise in Kubernetes, Docker, and Python or TypeScript to support distributed AI services and developer experience.
Design, build, and optimize enterprise AI solutions using LLMs (OpenAI, Azure OpenAI, Google Gemini), RAG architectures, vector databases, and Python-based cloud-native development.
DevOps Engineer for AI systems: designs and maintains CI/CD pipelines, observability, and cost/performance management for LLM/agentic applications, bridging POCs to production-grade deployments with Kubernetes and Terraform.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
