Intel is building the next generation of Hybrid Collaboration AI systems that intelligently integrate local and cloud AI. This role focuses on defining how AI workloads are planned, routed, and executed across environments, requiring collaboration with various teams to deliver optimized AI solutions.
Responsibilities:
- Build the hybrid AI collaboration layer connecting local AI and cloud AI
- Design dynamic orchestration for planning, routing, and execution
- Optimize AI workflows for latency, cost, privacy, and reliability
- Enable agent-based systems with local planning and hybrid execution
- Partner with product, systems, and runtime teams to ship production-ready platforms
- Engage with industry-leading AI providers for co-engineering
- Works with internal engineering teams and external partners, customers, and ISVs to deliver optimized AI solutions using Intel products with the goal of driving adoption of Intel products
- Researches technical trends and utilizes deep domain and market segment expertise to prototype solutions and develop AI software to enable hybrid collaboration AI
- Optimizes performance of AI models through deep knowledge and expertise of AI frameworks, algorithms, models, and related hardware
- Researches, develops, and adjusts new or existing AI models, code, parameters, and/or quantization to address issues and modify operations to enhance hybrid performance
- Partners with AI algorithm and framework engineers as needed to optimize endtoend AI models to Intel hardware features
- Serves as a trusted technical advisor and provides technical enabling
- Partners with Intel software and hardware product development teams to accelerate and optimize future products in AI and HPC domains by leading application preenabling and product hardening
- Delivers competitive and differentiated benchmark collateral and identify and drive key workloads into product requirements and architect innovative projection methodologies and tools
Requirements:
- Bachelor's degree in STEM field
- 8+ years hands-on experience on AI/ML algorithm development
- 4+ years of experience in NLP, LLM-based systems, or AI agent development
- Deep expertise in GenAI algorithms, solution architecture, and performance tuning
- Proven experience building custom AI tools, agents, or apps for real-world use cases
- Strong Python or C++ skills
- Problem-solving skills with a results-driven, customer-focused mindset
- Familiarity with client AI tools, cross-platform agents, or plugin ecosystems
- Agent orchestration, task routing, or scheduling systems
- Experience with RAG pipelines, vector databases (e.g., FAISS, Chroma), and embedding techniques
- Experience optimizing GenAI workloads for edge devices using xPU accelerators
- Experience with local LLMs (e.g., Mistral, Llama) or fine-tuning open-source models
- Experience in customer/partner support for GenAI workflow design and deployment
- Experience with frameworks such as LangChain, LlamaIndex, AutoGen, HuggingFace, and other APIs
- Experience in UX/UI or prompt engineering to improve human-AI interaction