Data Center AI Systems Engineer - Competitive Analysis

About Qualcomm

Qualcomm Middle East Information Technology Company LLC leads innovation by advancing technology to enable next-generation experiences and facilitate digital transformation toward a smarter, connected future.

Role Overview

We are seeking a Data Center AI Systems Engineer specializing in AI inference platforms and competitive benchmarking. This position entails evaluating, benchmarking, optimizing, and validating AI inference solutions leveraging Qualcomm AI accelerators. The role involves analyzing real-world deployments, assessing competitors, and generating data-driven insights regarding performance, scalability, ecosystem maturity, and operational efficiency in GenAI workloads such as LLMs, VLMs, RAG, and agentic applications.

Key Responsibilities

• Conduct comprehensive competitive analyses on Qualcomm AI inference hardware, software, model-serving frameworks, and deployment workflows.
• Analyze deployment patterns including LLM/VLM serving, RAG, agent-driven workflows, embedding services, multi-model applications, and enterprise pipelines to determine Qualcomm’s comparative advantages and gaps.
• Create robust benchmarking methodologies and oversee performance evaluations encompassing latency, TTFT, batching, throughput, concurrency, power and cost efficiency, including single-node and multi-node scaling.
• Compare Qualcomm solutions against competitors like NVIDIA and AMD focusing on deployment readiness, model framework compatibility, operational ease, and overall solution maturity.
• Investigate architectural trade-offs involving inference servers and orchestration layers, including key-value cache management, quantization, batching strategies, and distributed serving techniques.
• Prioritize model onboarding based on competitive usage trends, customer demands, and framework adoption across open-source and enterprise GenAI workloads.
• Develop and maintain reference architectures, deployment guides, sizing recommendations, and reproducible benchmark procedures for Qualcomm AI platforms.
• Collaborate across architecture, compiler, runtime, systems, product teams to translate market insights into product improvements, roadmap features, and ecosystem strategies.
• Troubleshoot system issues spanning model, framework, runtime, hardware, networking, memory, and orchestration layers to resolve performance bottlenecks.
• Prepare clear technical documentation including competitive analysis reports, leadership summaries, customer collateral, and gap analyses.
• Work closely with customer engineering, sales, business development, and ecosystem partners to support evaluations, proof-of-concepts, and deployments.
• Stay informed about the evolving AI inference ecosystem concerning models, serving frameworks, accelerator platforms, open-source projects, benchmarking standards, and market trends.

Qualifications and Experience

• Bachelor’s degree in Engineering, Computer Science, Data Science or a related discipline with at least 8 years of relevant experience.
• Alternatively, a Master’s degree with 4 or more years, or a PhD with a minimum of 4 years professional experience is acceptable.
• In-depth skills in Python programming and familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or ONNX.
• Practical knowledge of machine learning model development, deployment, and AI inference practices for datacenter workloads.
• Strong experience in system performance profiling, benchmarking, parallel computing, and workload analysis.
• Knowledge of Linux development environments, containerized deployments, and cloud-native infrastructure.
• Excellent analytical, communication, and teamwork capabilities to present findings effectively.
• Preferred: Sound expertise in GenAI enterprise inference including LLMs, VLMs, embeddings, diffusion models, RAG pipelines, and multi-turn agent workflows.
• Hands-on familiarity with AI accelerator platforms, including competitive products from NVIDIA and AMD.
• Experience with inference serving frameworks such as vLLM, Triton, TensorRT-LLM, KServe, Ray Serve, TorchServe, or similar tools.
• Comprehensive understanding of inference performance metrics: latency, batching, throughput, cache usage, scaling efficiency, and quantization.
• Background in designing benchmarks across multi-node setups and realistic customer workloads.
• Knowledgeable about distributed inference architectures involving tensor/pipeline/expert parallelism, autoscaling, routing, and orchestration.
• Experience using container orchestration (Docker, Kubernetes, Helm), CI/CD pipelines, GitOps, and observability tools.
• Strong ability to evaluate ecosystem readiness, tool maturity, documentation quality, deployment complexity, and supportability.
• Additional benefit if experienced in compiler and runtime optimization, graph lowering, operator fusion, or hardware-aware ML workload tuning.
• Skilled in generating customer-facing technical content, competitive positioning materials, deployment guides, and executive summaries.
• Proven cross-functional collaboration in matrix organizations engaging product, engineering, sales, and partner teams.

Employment Benefits

• Competitive salary including housing and transport allowances.
• Equity participation through Restricted Stock Units (RSUs) and performance bonuses.
• Generous parental leave: 16 weeks paid maternity leave and 6 weeks paid paternity leave.
• Employee stock purchase plans.
• Child education allowances.
• Relocation and immigration support where applicable.
• Life and medical insurance coverage.
• Reimbursements for health and recreational memberships.

Additional Information

Qualcomm is committed to equal opportunity employment and supports accessible hiring practices. Reasonable accommodations are provided for individuals with disabilities. Applicants are requested to respect company policies regarding confidential information. Recruiting agencies are not authorized to submit resumes for this position.