Posted:
9/25/2025, 7:00:56 PM
Location(s):
Penang, Malaysia
Experience Level(s):
Junior
Field(s):
AI & Machine Learning ⋅ Software Engineering
Workplace Type:
Hybrid
The ideal candidate is hands-on with AI systems engineering, has experience integrating multiple models and runtimes, and is passionate about building secure, scalable, and efficient AI solutions that power next-generation agentic applications.
Responsibilities
Hybrid AI Agent Development: Architect, build, and optimize AI agents that run seamlessly across device and cloud environments.
MCP Service Integration: Leverage and extend MCP services to enable flexible orchestration, tool integration, and agent coordination.
Agentic Routing & Planning: Implement routing logic and reasoning strategies to improve decision-making and planning across multi-agent and multi-model systems.
Model Runtime Engineering: Work with different model runtimes, frameworks, and backends to maximize performance.
Security & Compliance: Ensure model safety, sandboxing, data governance, and secure execution across device and cloud.
Optimization: Apply techniques like model quantization, pruning, distillation, and caching for efficiency across diverse environments.
Technical Evangelism: Contribute to best practices, design patterns, and technical documentation to support broader adoption of hybrid AI agent architectures.
2+ years hands-on experience on AI/ML algorithm development
1+ years of hands-on 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.
Excellent problem-solving skills with a results-driven, customer-focused mindset.
Familiarity with client AI tools, cross-platform agents, or plugin ecosystems.
Good to have skills:
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 inter
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.Website: https://www.intel.com/
Headquarter Location: Santa Clara, California, United States
Employee Count: 10001+
Year Founded: 1968
IPO Status: Public
Last Funding Type: Post-IPO Equity
Industries: Artificial Intelligence (AI) ⋅ Information Technology ⋅ Product Design ⋅ Semiconductor ⋅ Software