LLM & Agentic AI Performance Engineer
Intel · Posted Oct 16
Semiconductor manufacturing, microprocessors, data center solutions, and artificial intelligence infrastructure
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About the role
Intel's AI Solutions and Toolkit Engineering team, part of the Data Center organization, enables modern AI workloads and solutions on Intel platforms across LLM inference, Agentic AI, AI frameworks and runtimes, workload optimization, open-source software, and datacenter AI systems. The team bridges silicon-level benchmarking and optimization teams with teams building real-world AI solutions. This role owns end-to-end performance characterization and optimization of LLM and Agentic AI workloads, from Python-level frameworks and inference runtimes down to Linux, system architecture, memory, and hardware performance counters, turning findings into code contributions, configurations, and customer-ready solutions.
What you will do
- Characterize and optimize LLM and Agentic AI workloads across the complete software and hardware stack.
- Identify performance bottlenecks across AI frameworks, inference runtimes, operating systems, memory, compute, and platform architecture.
- Design and develop hardware-aware and hardware-agnostic optimizations for AI frameworks and runtimes.
- Optimize LLM inference techniques including KV-cache management, attention, continuous batching, and quantization.
- Work hands-on with serving stacks such as vLLM, SGLang, TGI, or equivalent technologies.
- Analyze host and accelerator performance using tools such as VTune, EMON/PMU, perf, top-down analysis, and roofline modeling.
- Debug complex performance issues spanning Python frameworks, native code, Linux, runtime libraries, and hardware.
- Convert performance findings into software changes, upstream contributions, BKCs, and reusable optimization guidance.
- Collaborate with open-source communities to upstream and integrate performance improvements.
- Translate silicon-level findings into actionable recommendations for framework developers, while bringing application and framework insights back to Intel platform and silicon teams.
Skills used in this role
What the employer is looking for
- BE +10 years / M.Tech +8 years in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline.
- Significant hands-on experience in performance engineering, systems optimization, or workload characterization on server-class platforms.
- Demonstrated ability to identify complex performance bottlenecks and deliver measurable performance improvements.
- Strong programming skills in Python and C++, or equivalent systems programming experience in C/Rust.
- Strong understanding of server architecture including cache hierarchy, memory bandwidth, NUMA, interconnects, and system-level performance behavior.
- Hands-on experience with Linux performance and system technologies such as affinity, huge pages, cgroups, eBPF, ftrace, perf, or equivalent tools.
Preferred qualifications
- Deep understanding of LLM inference, including KV-cache, paged attention, continuous batching and quantization such as INT8, INT4, or FP8.
- Hands-on experience modifying or optimizing AI serving stacks such as vLLM, SGLang, TGI, OpenVINO, or equivalent.
- Experience building, profiling, or optimizing Agentic AI systems using technologies such as LangGraph, CrewAI, AutoGen, MCP-based frameworks, or similar platforms.
- Experience with hardware counter-level performance analysis using VTune, EMON/PMU, perf, top-down analysis, or roofline modeling.
- Contributions to significant open-source projects, including upstream code contributions.
- Ability to communicate across abstraction layers, translating silicon-level findings for software developers and application-level requirements for hardware architects.
Benefits and support
- Compensation and benefits are detailed in the job posting
About Intel
Intel Corporation is a global technology leader focused on the design and manufacturing of microprocessors, integrated circuits, and advanced data center infrastructure. The company drives innovation across personal computing, artificial intelligence, and cloud ecosystems while operating a major semiconductor foundry business. Intel delivers foundational silicon and packaging solutions that power modern digital infrastructure worldwide.
- Industry
- Semiconductors
- Company size
- 10001+ employees
- Founded
- 1968
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Leadership
Lip-Bu Tan
Chief Executive Officer
Executive Vice President and Chief Financial Officer
Pushkar Ranade
Chief Technology Officer and Chief of Staff to the CEO
Executive Vice President – Chief Technology and Operations Officer, General Manager Intel Foundry
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