Intel currently has 84 active job listings related to artificial intelligence. The majority of these roles, 51%, are focused on serving infrastructure, with agents representing another significant portion at 24%. Engineering is the most frequent function for these positions. The company is actively hiring in the United States, China, and Mexico. Frequent technical tags include model serving, inference infrastructure, and agent orchestration. In the last 30 days, Intel has added 73 new AI roles, representing a 52% increase compared to the previous 30-day period.
Currently tracking 56 active AI roles, down 34% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $122k–$414k (avg $253k).
Intel currently has 59 active AI-related roles in our index. The most common open titles are: AI Software Engineering Intern (3), AI Software Engineer Intern (2), GenAI Software Solutions Engineer (2), Graduate Talent (GenAI Software Solutions Engineer) (2), AI Algorithm Engineer. Most positions are in Engineering and Research.
Intel's active AI hiring is concentrated in: serving infrastructure (49%), agents (29%), application (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Intel is hiring AI talent in: United States (28 roles), China (7 roles), Mexico (6 roles), Malaysia (6 roles).
Job postings at Intel most frequently reference: model serving, inference infra, agent orchestration, rag, tool use.
In the past 30 days, Intel has posted 28 new AI-related roles. That is a -63% change versus the prior 30 days (75 → 28).
| Title | Stage | AI score |
|---|---|---|
| AI Software Engineering Intern This internship focuses on developing and enabling Agentic AI systems on AI PC platforms. Responsibilities include setting up AI environments, experimenting with AI models and applications, and supporting pretraining and task learning pipelines. The role emphasizes hands-on engineering across AI infrastructure, system setup, and agent-oriented AI workloads, contributing to client AI software ecosystem development. | AgentPost-train | 8 |
| Senior GenAI Software Solutions Engineer Senior GenAI Software Solutions Engineer role focused on architecting, building, and optimizing hybrid AI agents that run across device and cloud environments. Responsibilities include MCP service integration, agentic routing and planning, model runtime engineering, security and compliance, and optimization techniques like quantization and distillation. Requires 5+ years in AI/ML algorithm development and 2+ years in NLP, LLM-based systems, or AI agent development. |
| Agent |
| 8 |
| Senior GenAI Software Architect Senior GenAI Software Architect role focused on building and architecting machine learning products and solutions, with a strong emphasis on GenAI algorithms, LLM-based systems, and AI agent development. The role involves translating ML models into software, optimizing for edge devices, and supporting customer/partner deployments. | AgentPost-train | 8 |
| GenAI Software Architect GenAI Software Architect role at Intel, focusing on building and optimizing AI/ML-based products and solutions, particularly LLM-based systems and AI agents. Requires expertise in GenAI algorithms, solution architecture, performance tuning, and experience with frameworks like LangChain and RAG pipelines. The role involves developing and deploying machine learning models and methods into software, with a focus on real-world use cases and edge device optimization. | Agent | 8 |
| AI Software Engineer – Agentic AI System AI Software Engineer focused on building infrastructure and tooling for an end-to-end evaluation ecosystem for agentic AI frameworks. Responsibilities include developing scalable deployment and orchestration systems, data pipelines, dashboards, observability tooling, and automating evaluation pipelines for AI agent frameworks and model-serving systems. | AgentEval Gate | 7 |
| Software Engineer - Agent Harness Software Engineer to build the 'harness' for agentic AI systems, focusing on the agent loop, tool integration, context management, and scheduling. The role emphasizes creating a model-agnostic framework for hybrid local and cloud intelligence, with a strong focus on core product engineering for an agent framework. | Agent | 7 |
| AI Algorithm Engineer AI Algorithm Engineer role focused on designing, building, and integrating generative AI agents and platforms using local and cloud-based LLMs. The role involves developing AI-powered products, focusing on agent orchestration, tool usage, RAG, and system optimization, and translating AI logic into production-quality software. | Agent | 7 |
| GenAI Software Solutions Engineer This role focuses on designing, building, and integrating generative AI agents and platforms using both local and cloud-based LLMs. The engineer will develop AI-powered products, focusing on agent orchestration, tool usage, RAG, and system optimization, translating AI logic into production-quality software. The position is for a fresh graduate or early-career professional with basic understanding of GenAI and LLMs, and programming experience in Python/C++. | Agent | 7 |
| Graduate Talent (GenAI Software Solutions Engineer) This role focuses on designing, building, and integrating generative AI agents and platforms, leveraging both local and cloud-based LLMs. The engineer will develop AI-powered products and solutions for real-world use cases, focusing on agent orchestration, tool usage, RAG, and system optimization. Responsibilities include end-to-end development from implementation to deployment, translating AI logic into production-quality software. | Agent | 7 |
| GenAI Software Solutions Engineer This role focuses on designing, building, and deploying generative AI agents and platforms, integrating local and cloud-based LLMs. It involves developing AI-powered products for intelligent reasoning and automation, with an emphasis on agent orchestration, tool usage, RAG, and system optimization. The position requires end-to-end software development, including implementation, testing, debugging, documentation, and deployment, for a fresh graduate or early-career engineer. | Agent | 7 |
| Graduate Talent (GenAI Software Solutions Engineer) This role focuses on designing, building, and integrating generative AI agents and platforms, leveraging both local and cloud-based LLMs. The engineer will develop AI-powered products and solutions for real-world use cases, focusing on agent orchestration, tool usage, RAG, and system optimization. Responsibilities include end-to-end development, translating AI logic into production software, and deploying AI services. | Agent | 7 |
| AI Tools Development Intern Intern role focused on the development, validation, and deployment of AI tools such as GenAI assistants, RAG-based knowledge tools, and workflow automation agents within an enterprise AI context. Requires basic knowledge of ML/GenAI concepts and Python programming. | Agent | 7 |
| Image Processing Engineer (C++/Linux) Image Processing Engineer with C++/Linux experience to develop and implement computer vision algorithms for nanometer-scale metrology applications in mask and semiconductor manufacturing. The role involves algorithm development, programming, software tool development, testing, documentation, and user interaction to improve quality control and process development. | Agent | 7 |
| Sr. Security Architect Sr. Security Architect role focused on applying AI-driven tools to enhance security architecture for Client and Data Center SoCs, including firmware and low-level hardware/software. The role involves using AI for vulnerability identification, code analysis, threat modeling, and defining security specifications, aiming to discover risks earlier and more broadly than traditional methods. | Agent | 7 |
| Infrastructure and DevOps Engineer This role focuses on building and maintaining scalable CI/CD systems and infrastructure for wireless connectivity solutions. A key aspect is designing and implementing AI-driven DevOps solutions to improve developer productivity, such as failure analysis, pipeline intelligence, workflow automation, or agent-based systems. The role involves extensive work with Jenkins, Kubernetes, Elastic Stack, Prometheus, Grafana, Ansible, Python, and Bash in Linux environments. | Agent | 5 |
| Analytics and AI Solution Architect This role focuses on developing and implementing cloud-native analytical applications and solutions, with a strong emphasis on leveraging data engineering and cloud platforms. A key aspect involves designing and building pipelines for structured and unstructured data, including the use of Vector databases within a Retrieval Augmented Generative AI architecture. The role also involves applying Lambda architecture, database design, and data modeling, and collaborating on AI/ML infrastructure and big data integrations. | AgentData | 5 |