Find your next AI Engineering role
2+ open roles · 369+ companies hiring
2 open positions
AI Native Software Engineer
Accenture
We are seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using Generative and Agentic AI frameworks that drive innovation, efficiency, and business transformation. This role involves leading AI-driven solution design and delivery by applying GenAI and Agentic AI to address complex business challenges, automate processes, and integrate intelligent insights into enterprise workflows for measurable impact. The ideal candidate will have robust experience in .NET Core, MVC, and Python, with working knowledge of front-end technologies like React or Angular, and a foundational understanding of AI integration. This role emphasizes active coding, solution implementation, and collaboration across application development, infrastructure, and integration in multi-cloud environments.
AI Native Software Engineer
Accenture
We are seeking a dynamic Mid-Level Application Architects / Senior Developers with a strong focus on hands-on development and practical solution design. The ideal candidate will have robust experience in .NET Core, MVC, and Python, with working knowledge of front-end technologies like React or Angular, and a foundational understanding of AI integration. This role emphasizes active coding, solution implementation, and collaboration across application development, infrastructure, and integration in multi-cloud environments (AWS, Azure, Google Cloud) to deliver scalable, secure enterprise applications. AI Powered Tech Talent
Frequently asked questions
What counts as an AI Engineering job?
AI Job Board lists engineering roles that build, deploy, or operate AI/ML systems — including LLM engineering, RAG (retrieval-augmented generation), AI agents, prompt engineering, AI infrastructure and MLOps, model serving/inference, and fine-tuning. It excludes non-engineering functions like AI sales or marketing roles.
What is the difference between an AI Engineer and a Machine Learning Engineer?
An AI Engineer typically builds applications on top of existing models — LLM integration, RAG pipelines, agent orchestration, and prompt design. A Machine Learning Engineer more often trains, fine-tunes, or productionizes custom models. Many companies use the titles interchangeably, so search both when browsing.
Does AI Job Board include AI infrastructure and MLOps roles?
Yes. Titles such as AI Infrastructure Engineer, ML Platform Engineer, GPU Infrastructure Engineer, Inference Engineer, MLOps Engineer, and AI Site Reliability Engineer are all covered — these roles focus on the systems that serve and scale AI models rather than building models themselves.
Are remote AI and ML jobs available?
Yes. Filter by "Remote" on the jobs page to see fully remote AI/ML engineering roles, or browse the remote jobs feed directly.
What skills are most in demand for AI engineering roles?
The most commonly requested skills are LLM APIs (OpenAI, Anthropic, Gemini), RAG and vector databases (Pinecone, Weaviate, Qdrant), agent frameworks (LangGraph, CrewAI, AutoGen), inference/serving tools (vLLM, Ray Serve, TensorRT-LLM), and fine-tuning. Use the skill filters on the jobs page to browse by specific technology.
How fresh are the job listings?
Listings are sourced continuously from company career pages and refreshed automatically. Each job shows when it was posted, and the sitemap and API expose last-updated timestamps for every posting.
How much do AI Engineers get paid?
Compensation varies widely by role, seniority, and location. Where employers disclose a salary range, it is shown directly on the job listing — filter by salary range on the jobs page to narrow results to your target compensation.