Principal Software Engineer – Inference

Hewlett Packard Enterprise

. Define and own the technical direction of LLM serving deployment, including engine integration, continuous batching, KV cache management and reuse, and quantized execution .

Posted 9/16/2026full-timeSpring • Colorado • United StatesLead💰 $152,000 - $349,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in LLM inference runtime development and deployment, with a strong focus on performance optimization, distributed inferencing strategies, and orchestration within enterprise environments. Proficient in mentoring engineering teams and leading architectural reviews to drive technical direction.

Highest-signal resume keywords

LLM Inference Runtime DevelopmentKubernetes Platform ArchitecturesGo ProgrammingPython ProgrammingContinuous Batching

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LLM Inference EnginesQuantizationTensor ParallelismPipeline ParallelismKV Cache ManagementC++/CUDA DebuggingPerformance EngineeringProfiling Multi-Tier ApplicationsNCCL Collective OperationsSpeculative Decoding

Soft Skills

Analytical AbilitiesProblem-Solving SkillsMentoring

Tools & Technologies

NsightRDMAGPUDirect StorageInfiniBandRoCE

Industry Keywords

Software EngineeringProduction Model ServingEnterprise Software DeliveryAir-Gapped EnvironmentsSovereign Environments

Tech Stack

Tools & technologies

KubernetesPythonC++Go

About the role

Key responsibilities & impact

Define and own the technical direction of LLM serving deployment, including engine integration, continuous batching, KV cache management and reuse, and quantized execution
Partner with inference performance engineering teams and own time-to-first-token, inter-token latency, throughput per GPU, and P95/P99 tail latency
Define distributed inferencing strategy, including disaggregated prefill/decode, tensor and pipeline parallelism, and KV cache offload across GPU memory, host memory, and RDMA-attached storage
Evaluate emerging runtimes, quantization schemes, speculative decoding, and mixture-of-experts serving, deciding whether to adopt, develop in-house, or decline them
Define the orchestration layer, including model admission, GPU scheduling and partitioning, cache-aware request routing, and autoscaling
Mentor engineers, lead design and architecture reviews, and present technical direction to business unit and executive audiences
Lead the model runtime within HPE AI Essentials, an inference platform for enterprises operating large language models on owned infrastructure, including air-gapped and sovereign environments

Requirements

What you’ll need

Minimum of 12 years of experience in Software Engineering, including +1 years working directly on LLM inference runtimes or production model serving
Production experience with LLM inference engines such as vLLM, SGLang, TensorRT-LLM, TGI, or NVIDIA NIM, including modification of engine internals
Comprehensive understanding of continuous batching, paged attention, KV cache reuse and prefix caching, chunked prefill, quantization, and speculative decoding
Knowledge of tensor and pipeline parallelism, NCCL collective operations, GPU memory hierarchy, and interconnect characteristics
Expert proficiency in Kubernetes platform architectures, including operators, custom resources, controllers, and scheduling
Strong programming proficiency in Go and Python
Ability to read, debug, and profile C++/CUDA using tools such as Nsight
Experience debugging and profiling multi-tier application workloads such as RAG and Agents
Excellent analytical, debugging, and problem-solving abilities
Degree in Computer Science or related field
Preferred: upstream contributions to vLLM, SGLang, TensorRT-LLM, LLM-D, LMCache, or KServe
Preferred: disaggregated prefill/decode serving or KV cache offload and reuse at scale
Preferred: RDMA, GPUDirect Storage, InfiniBand, or RoCE
Preferred: MIG, fractional GPU allocation, and multi-tenant GPU isolation
Preferred: on-premises, air-gapped, or regulated enterprise software delivery

Benefits

Comp & perks

Comprehensive health, financial, and emotional wellbeing benefits
Personal and professional development programs
Flexible work and personal needs management
Inclusive workplace culture
Employee benefits information available through HPE Rewards