About the Role
We are looking for a talented and motivated AI System Performance Architect. The role owns the end-to-end understanding of AI training and inference systems, sitting where serving strategy, parallelism, collective communication, and interconnect behavior come together. Through analytical modelling and multi-GPU simulation, the candidate translates SLA and deployment targets into concrete architectural guidance for Intel's future AI platforms. Strong analytical skills and the ability to present performance findings and configuration recommendations to engineering and leadership teams are essential.
Key Responsibilities
• Own end-to-end understanding of the AI training/inference system and build analytical models and multi-GPU simulation - including MPI/collective communication (allgather, allreduce, all-to-all) and interconnect contention - to project performance, expose architectural bottlenecks, and recommend optimal Intel system configurations.
• Model inferencing strategies - static batching, continuous batching, disaggregated serving, and chunked prefill - across frameworks such as vLLM and SGLang, covering agentic inferencing, prefix caching, and multi-turn flows.
• Cover data, pipeline, tensor, and expert parallelism and their communication patterns.
• Drive studies against SLA targets - batch size, TTFT, TPOT, ISL/OSL, and TPS.
• Analyse regression run traces and find patterns in utilization counters across SLA operating points to identify architectural bottlenecks.
• Perform what-if analysis by sweeping core count, memory/cache capacity and bandwidth, fabric bandwidth, GPU interconnect, and deployment options; deliver optimization and optimal architecture recommendations.
• Scout whitepapers, blogs, and conferences; keep self and team updated on AI innovations applicable to Intel's end-to-end system.
Required Qualifications
• Bachelor's, master's or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Bachelors with 8+ yrs, master’s with 6+ years and Ph.D. with 3+ years of experience in system performance modelling, AI workload analysis, or hardware architecture.
• Strong proficiency in Python, with the ability to build modular, maintainable analytical models and simulation frameworks.
• Solid understanding of LLM inference and training mechanics: prefill vs. decode, KV cache, batching policies, and quantization.
• Working knowledge of distributed parallelism strategies and their communication patterns.
• Familiarity with multi-GPU interconnect architectures (NVLink, PCIe, CXL, or equivalent).
• Understanding of SoC and platform fundamentals: core count scaling, cache/memory capacity and bandwidth, and fabric behavior.
Good-to-Have Skills
• Experience building discrete-event simulators for multi-node or multi-accelerator systems.
• Familiarity with performance profiling tools (e.g., Intel VTune, NVIDIA Nsight, or similar).
• Prior experience in a semiconductor or hardware company working on AI accelerator or platform products.
Join Intel and be part of a team that is shaping the future of data-driven innovation. Seize the opportunity to make a meaningful impact through your expertise and creativity-apply today.
Job Type:Experienced HireShift:Shift 1 (India)Primary Location: India, BangaloreAdditional Locations:Posting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/A
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.*
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.Skills Required
- Bachelor's, master's, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field
- Bachelor's degree with 8+ years, master's degree with 6+ years, or PhD with 3+ years of experience in system performance modeling, AI workload analysis, or hardware architecture
- Strong proficiency in Python and ability to build modular, maintainable analytical models and simulation frameworks
- Understanding of LLM inference and training mechanics, including prefill, decode, KV cache, batching policies, and quantization
- Working knowledge of distributed parallelism strategies and communication patterns
- Familiarity with multi-GPU interconnect architectures such as NVLink, PCIe, CXL, or equivalent
- Understanding of SoC and platform fundamentals, including core scaling, cache and memory capacity, bandwidth, and fabric behavior
- Experience building discrete-event simulators for multi-node or multi-accelerator systems
- Familiarity with performance profiling tools such as Intel VTune, NVIDIA Nsight, or similar
- Experience in a semiconductor or hardware company working on AI accelerator or platform products
Intel Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Intel and has not been reviewed or approved by Intel.
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Leave & Time Off Breadth — Sabbaticals and paid time off are highlighted as signature elements, with an established program offering four weeks after four years or eight weeks after seven years. This distinctive time off is positioned as a meaningful part of the overall package.
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Parental & Family Support — Paid bonding leave of 12 weeks and a New Parent Reintegration program, plus fertility benefits around $40,000 and up to $15,000 adoption reimbursement with no lifetime cap, are clearly stated. These programs are presented as standout components alongside broader family support resources.
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Healthcare Strength — Multiple medical plan options with 2026 updates, a shift to Spring Health for EAP, and in‑network virtual medical visits covered at 100% beginning in 2026 indicate a comprehensive offering. These features signal an emphasis on robust medical access and mental health support.
Intel Insights
What We Do
Our mission is to shape the future of technology to help create a better future for the entire world, that’s the power of Intel Inside. With more ingenuity and creativity inside, our work is at the heart of countless innovations. From major breakthroughs to things that make everyday life better— they’re all powered by Intel technology. With a career at Intel, you can help make the future more wonderful for everyone.
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