Senior Level SOC Analyst Jobs
Senior level soc analyst jobs put seasoned security professionals in charge of threat detection strategy, incident response leadership, and the analysts and processes that keep enterprise environments secure. Openings concentrate in Electronics & Hardware, Technology & Software, and Consulting & Professional Services, with a mix of on-site, hybrid, and remote positions available, and employers like Apple, Intel, and NVIDIA hiring at this level now.
Find Senior Level SOC Analyst JobsOverview
Open roles253+
Top stateCalifornia
Top employerApple
Top cityAustin, TX
Work type73% On-site
Top industryElectronics
Showing 5 of 253+ Senior Level SOC Analyst jobs
Principal SoC Performance Architect-Microbenchmarks
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New 1m ago
AMD
Principal SoC Performance Architect-Microbenchmarks
Austin, Texas
New 1m ago
Security Operations Center (SOC) Manager
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New 1m ago
Metro One LPSG
Security Operations Center (SOC) Manager
New Albany, Ohio
New 1m ago
Senior Cyber Security Analyst - Threat Management (remote)
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New 1m ago
First Citizens Bank
Senior Cyber Security Analyst - Threat Management (remote)
Raleigh, North Carolina
New 1m ago
Senior Staff Engineer, SoC Architecture – Memory Subsystem and Interconnect
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Samsung Research America
Senior Staff Engineer, SoC Architecture – Memory Subsystem and Interconnect
Mountain View, California
New 1m ago
SoC Product Architect, Memory Ecosystem
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NVIDIA
SoC Product Architect, Memory Ecosystem
Santa Clara, California
New 1m ago
New 1m ago
Principal SoC Performance Architect-Microbenchmarks
AMD·Austin, Texas
Job functions:
10+ yrs exp.
Doctoral degree in Computer Science
5,001-10,000 employees
Job Description
Overview:
AMD is looking for an outstanding technical contributor to drive performance analysis, characterization, and optimization of next-generation Data Center GPU (DCGPU) platforms.
THE PERSON:
ACADEMIC CREDENTIALS:
This role is not eligible for visa sponsorship.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
Responsibilities:
THE ROLE:
AMD is looking for an outstanding technical contributor to drive performance analysis, characterization, and optimization of next-generation Data Center GPU (DCGPU) platforms.
This role focuses on extracting maximum performance across the full system stack—including hardware, firmware, drivers, runtime, libraries, and workloads—through deep architectural understanding and data-driven methodologies. The engineer will develop and maintain microbenchmarks and system-level workloads spanning pre-silicon and post-silicon environments to enable performance validation, debug, and optimization.
THE PERSON:
As a passionate and technically strong Principal SoC Performance Engineer, you will work on highly parallel SoC architectures, leveraging deep understanding of GPU compute, memory hierarchy, and interconnects to analyze and optimize performance across AI and HPC workloads.
You will be responsible for building microbenchmark suites and workload-driven analysis frameworks that expose performance characteristics of GPU subsystems (compute, memory, IO, interconnect, collectives) and ensure continuity across pre-silicon models, emulation, and post-silicon systems.
The ideal candidate combines strong hardware/software co-design expertise with hands-on experience in performance analysis, profiling, and system-level debugging. You are expected to identify bottlenecks across the entire stack—from kernels to runtime to hardware—and translate insights into actionable improvements for both current and future architectures.
You thrive in a fast-paced environment, are highly data-driven, and have a deep curiosity for understanding “why” performance behaves the way it does.
KEY RESPONSIBILITIES:
Performance Analysis & Optimization- Analyze and optimize performance of DCGPU systems across AI training, inference, and HPC workloads
- Identify bottlenecks across hardware, firmware, drivers, runtime, libraries, and applications
- Perform deep kernel-level and system-level profiling to understand performance behavior
- Provide actionable insights to architecture, software, and design teams to improve performance
Microbenchmark & Workload Development
- Design and develop targeted microbenchmarks to characterize GPU subsystems (compute, memory, interconnect, collectives)
- Build representative system-level workloads reflecting real-world AI/HPC use cases
- Ensure microbenchmarks correlate to application-level performance and architectural intent
- Maintain and evolve benchmark suites across multiple GPU generations
Pre-Silicon & Post-Silicon Continuity
- Enable performance validation in pre-silicon environments (simulation/emulation/models)
- Correlate performance data across pre-silicon models and post-silicon measurements
- Develop methodologies to reuse workloads and microbenchmarks across the full lifecycle
- Support bring-up and early silicon performance characterization
Full-Stack Performance Engineering
- Work across the entire software stack: compiler, runtime, libraries, drivers, and firmware
- Collaborate with ROCm / AI frameworks / kernel teams to improve performance
- Analyze interactions between workload characteristics and hardware execution
- Optimize key kernels (e.g., GEMMs, collectives, attention) and system-level behavior
Tooling & Infrastructure
- Develop and enhance performance measurement, profiling, and analysis tools
- Enable scalable, repeatable workflows for benchmarking and analysis
- Build automation for performance regression tracking and reporting
- Contribute to unified infrastructure spanning pre-silicon and post-silicon environments
Cross-Functional Collaboration
- Partner with SoC architecture, GPU IP, software, and system teams
- Influence design decisions using data-driven performance insights
- Collaborate with competitive analysis teams to understand gaps vs. industry platforms
Performance Modeling & Insights
- Develop strong intuition and/or models for performance scaling and limits
- Translate performance data into architectural feedback for future GPU designs
- Support competitive benchmarking and performance projections
PREFERRED EXPERIENCE:
- 10–15+ years of experience in performance engineering for GPUs, HPC systems, or highly parallel SoCs
- Strong understanding of GPU architecture, parallel computing, and memory hierarchies
- Experience with microbenchmark development and system-level workload analysis
- Hands-on experience with performance profiling tools (rocprof, Nsight, perf, etc.)
- Experience analyzing AI/HPC workloads (LLMs, training, inference, communication libraries like RCCL/NCCL)
- Strong background in hardware/software co-design and performance optimization
- Familiarity with pre-silicon (simulation/emulation/models) and post-silicon performance workflows
- Programming expertise in C/C++, Python; experience with GPU programming models (HIP, CUDA, OpenCL)
- Strong analytical and debugging skills with a data-driven mindset Experience working across full software stack (compiler runtime kernels
- system)
- Exposure to performance modeling, scaling analysis, or competitive benchmarking is a plus
POSITION REQUIREMENTS:
- Proven experience working on highly parallel compute systems or SoCs (GPUs preferred)
- Experience developing and maintaining microbenchmarks tied to architectural features
- Strong exposure to performance analysis across pre-silicon and post-silicon environments
- Solid understanding of GPU compute, memory systems, and interconnect architectures
- Experience with profiling, tracing, and performance counter analysis
- Ability to debug complex system-level performance issues across multiple layers
- MS/PhD in Computer Engineering, Computer Science, or related field
- Excellent communication skills and ability to present complex performance insights clearly
ACADEMIC CREDENTIALS:
- Bachelor’s or Master’s degree in related discipline preferred
This role is not eligible for visa sponsorship.
#LI-RL1
Qualifications:
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
AMD
Principal SoC Performance Architect-Microbenchmarks
Austin, Texas
New 1m ago5,001-10,000 employees
Job functions:
10+ yrs exp.
Doctoral degree in Computer Science
Job Description
Overview:
AMD is looking for an outstanding technical contributor to drive performance analysis, characterization, and optimization of next-generation Data Center GPU (DCGPU) platforms.
THE PERSON:
ACADEMIC CREDENTIALS:
This role is not eligible for visa sponsorship.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
Responsibilities:
THE ROLE:
AMD is looking for an outstanding technical contributor to drive performance analysis, characterization, and optimization of next-generation Data Center GPU (DCGPU) platforms.
This role focuses on extracting maximum performance across the full system stack—including hardware, firmware, drivers, runtime, libraries, and workloads—through deep architectural understanding and data-driven methodologies. The engineer will develop and maintain microbenchmarks and system-level workloads spanning pre-silicon and post-silicon environments to enable performance validation, debug, and optimization.
THE PERSON:
As a passionate and technically strong Principal SoC Performance Engineer, you will work on highly parallel SoC architectures, leveraging deep understanding of GPU compute, memory hierarchy, and interconnects to analyze and optimize performance across AI and HPC workloads.
You will be responsible for building microbenchmark suites and workload-driven analysis frameworks that expose performance characteristics of GPU subsystems (compute, memory, IO, interconnect, collectives) and ensure continuity across pre-silicon models, emulation, and post-silicon systems.
The ideal candidate combines strong hardware/software co-design expertise with hands-on experience in performance analysis, profiling, and system-level debugging. You are expected to identify bottlenecks across the entire stack—from kernels to runtime to hardware—and translate insights into actionable improvements for both current and future architectures.
You thrive in a fast-paced environment, are highly data-driven, and have a deep curiosity for understanding “why” performance behaves the way it does.
KEY RESPONSIBILITIES:
Performance Analysis & Optimization- Analyze and optimize performance of DCGPU systems across AI training, inference, and HPC workloads
- Identify bottlenecks across hardware, firmware, drivers, runtime, libraries, and applications
- Perform deep kernel-level and system-level profiling to understand performance behavior
- Provide actionable insights to architecture, software, and design teams to improve performance
Microbenchmark & Workload Development
- Design and develop targeted microbenchmarks to characterize GPU subsystems (compute, memory, interconnect, collectives)
- Build representative system-level workloads reflecting real-world AI/HPC use cases
- Ensure microbenchmarks correlate to application-level performance and architectural intent
- Maintain and evolve benchmark suites across multiple GPU generations
Pre-Silicon & Post-Silicon Continuity
- Enable performance validation in pre-silicon environments (simulation/emulation/models)
- Correlate performance data across pre-silicon models and post-silicon measurements
- Develop methodologies to reuse workloads and microbenchmarks across the full lifecycle
- Support bring-up and early silicon performance characterization
Full-Stack Performance Engineering
- Work across the entire software stack: compiler, runtime, libraries, drivers, and firmware
- Collaborate with ROCm / AI frameworks / kernel teams to improve performance
- Analyze interactions between workload characteristics and hardware execution
- Optimize key kernels (e.g., GEMMs, collectives, attention) and system-level behavior
Tooling & Infrastructure
- Develop and enhance performance measurement, profiling, and analysis tools
- Enable scalable, repeatable workflows for benchmarking and analysis
- Build automation for performance regression tracking and reporting
- Contribute to unified infrastructure spanning pre-silicon and post-silicon environments
Cross-Functional Collaboration
- Partner with SoC architecture, GPU IP, software, and system teams
- Influence design decisions using data-driven performance insights
- Collaborate with competitive analysis teams to understand gaps vs. industry platforms
Performance Modeling & Insights
- Develop strong intuition and/or models for performance scaling and limits
- Translate performance data into architectural feedback for future GPU designs
- Support competitive benchmarking and performance projections
PREFERRED EXPERIENCE:
- 10–15+ years of experience in performance engineering for GPUs, HPC systems, or highly parallel SoCs
- Strong understanding of GPU architecture, parallel computing, and memory hierarchies
- Experience with microbenchmark development and system-level workload analysis
- Hands-on experience with performance profiling tools (rocprof, Nsight, perf, etc.)
- Experience analyzing AI/HPC workloads (LLMs, training, inference, communication libraries like RCCL/NCCL)
- Strong background in hardware/software co-design and performance optimization
- Familiarity with pre-silicon (simulation/emulation/models) and post-silicon performance workflows
- Programming expertise in C/C++, Python; experience with GPU programming models (HIP, CUDA, OpenCL)
- Strong analytical and debugging skills with a data-driven mindset Experience working across full software stack (compiler runtime kernels
- system)
- Exposure to performance modeling, scaling analysis, or competitive benchmarking is a plus
POSITION REQUIREMENTS:
- Proven experience working on highly parallel compute systems or SoCs (GPUs preferred)
- Experience developing and maintaining microbenchmarks tied to architectural features
- Strong exposure to performance analysis across pre-silicon and post-silicon environments
- Solid understanding of GPU compute, memory systems, and interconnect architectures
- Experience with profiling, tracing, and performance counter analysis
- Ability to debug complex system-level performance issues across multiple layers
- MS/PhD in Computer Engineering, Computer Science, or related field
- Excellent communication skills and ability to present complex performance insights clearly
ACADEMIC CREDENTIALS:
- Bachelor’s or Master’s degree in related discipline preferred
This role is not eligible for visa sponsorship.
#LI-RL1
Qualifications:
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
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Who's Hiring
- Apple84
- Intel21
- NVIDIA9
- Micron Technology7
- Adobe4
Top Industries Hiring
- Electronics & Hardware133
- Technology & Software36
- Consulting & Professional Services22
- Banking & Financial Services6
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Senior Level SOC Analyst Jobs: Frequently Asked Questions
How do I get a senior level soc analyst job?
Employers hiring at the senior level want candidates who have led incident response efforts, mentored junior analysts, and owned detection engineering or threat hunting programs. Hands-on experience with SIEM platforms, EDR tooling, and cloud security is expected, not a differentiator. What sets candidates apart at this stage is demonstrated ownership of outcomes, the ability to build or improve SOC processes, and a history of cross-functional collaboration with engineering and leadership teams.
Which companies hire senior level soc analysts?
Companies hiring senior level soc analysts right now include Apple, Intel, and NVIDIA, based on current listings on Migrate Mate as of June 2026. Hiring at this level comes primarily from large enterprises, managed security service providers, financial institutions, defense contractors, and technology companies with mature security operations programs.
Are there remote senior level soc analyst jobs?
Yes, though availability varies by employer and the sensitivity of the work involved. About 27% of senior level soc analyst openings are remote or hybrid as of June 2026, reflecting strong demand for experienced analysts who can operate independently without on-site supervision. Roles tied to classified environments or high-compliance industries tend to require more in-person presence.
What makes a soc analyst role senior level?
Senior level soc analyst roles are defined by scope, ownership, and leadership responsibility. Rather than executing tasks assigned by others, senior analysts design detection logic, lead complex incident investigations, set response playbooks, and mentor junior and mid-level team members. They are expected to identify gaps in coverage, recommend tooling improvements, and communicate risk clearly to stakeholders outside the security team.
Which industries hire the most senior level soc analysts?
Senior level soc analyst roles concentrate in Electronics & Hardware, Technology & Software, and Consulting & Professional Services, based on current listings on Migrate Mate as of June 2026. These sectors drive hiring at this level because they operate at scale with complex regulatory requirements, high-value data environments, and mature security programs that need experienced practitioners to lead day-to-day operations.