---
title: 'Senior Software Engineer, Compute Platform at Moonlite'
canonical: 'https://feeny.ai/job/senior-software-engineer-compute-platform-moonlite-chicago-t61j0gcp1sm1'
type: 'job'
last_seen: '2026-09-10'
---

# Senior Software Engineer, Compute Platform at Moonlite

- **Company:** Moonlite
- **Location:** Chicago, IL
- **Work type:** remote
- **Posted:** 2025-10-31
- **Last confirmed live:** 2026-09-10
- **Apply:** https://job-boards.greenhouse.io/moonlite/jobs/4971679008

## Job description

Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads.We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance.

Your Role:

You will be instrumental in building out our GPU-accelerated compute platform that powers distributed AI training and inference, large-scale simulations, and computational research workloads. Working closely with product, your platform team members, and infrastructure specialists, you’ll design and implement the compute orchestration layer that manages GPU clusters, bare-metal provisioning, and resource scheduling-enabling researchers and engineers to programmatically access high-performance compute resources with cloud-like simplicity.

Job Responsibilities

- Compute Orchestration Systems: Design and build scalable compute orchestration platforms that manage GPU clusters, bare-metal server provisioning, and resource allocation across co-located infrastructure environments.
- Resource Management & Scheduling: Implement intelligent workload scheduling, resource allocation, and optimization algorithms that maximize GPU utilization while maintaining performance guarantees for research and training workloads.
- Research Cluster Provisioning: Design and implement systems for provisioning and managing research computing environments including Kubernetes and SLURM clusters, enabling automated deployment, resource scheduling, and workload orchestration for distributed AI training and HPC workloads.
- GPU Platform Engineering: Develop platform capabilities for managing latest-generation NVIDIA GPU configurations (H100, H200, B200, B300), including GPU resource management, multi-tenant isolation, and integration with compute orchestration systems.
- Bare-Metal Lifecycle Management: Build automation and tooling for complete bare-metal server lifecycle management – from initial provisioning and configuration through ongoing operations, updates, and resource reallocation.
- Performance-Critical Systems: Optimize compute platform components for high-throughput and low-latency performance, ensuring research workloads achieve near-bare-metal efficiency in virtualized or containersized environments.
- Platform APIs & Integration: Develop robust APIs and SDKs that enable researchers to programmatically provision and manage compute resources, integrating seamlessly with existing workflows and research infrastructure.
- Observability & Monitoring: Implement comprehensive monitoring and telemetry systems for compute resources, providing visibility into GPU virtualization, workload performance and infrastructure health.
- Multi-Tenancy and Isolation: Build enterprise-grade multi-tenant compute isolation, security boundaries, and resource quotas that enable safe sharing of GPU infrastructure across teams and organizations.

## Requirements

- Experience: 5+ years in software engineering with proven experience building compute platforms, container orchestration systems, or distributed compute infrastructure for production environments.
- Compute Platform Engineering: Strong background in building compute orchestration, resource scheduling, or workload management systems at scale.
- Kubernetes & Container Orchestration: Strong familiarity with Kubernetes architecture, container orchestration concepts, and experience deploying workloads in Kubernetes environments. Understanding of pods, deployments, services, and basic Kubernetes operations.
- Programming Skills: Experience with Go, C/C++, Python, or Rust for performance-critical components is highly valued.
- Linux & Systems Programming: Strong experience with Linux in production environments, including systems for programming, performance optimization, and low-level resource management.
- Virtualization & Containers: Deep knowledge of virtualization technologies (KVM, Xen), container runtimes, and orchestration platforms.
- GPU Computing Fundamentals: Understanding of GPU architectures, CUDA programming (where/when needed), and GPU resource management – or a strong ability to learn quickly.
- Bare-Metal Infrastructure: Experience with bare-metal provisioning, out-of-band management systems, and hardware abstraction layers.
- Problem-Solving & Architecture: Demonstrated ability to solve complex performance and scalability challenges while balancing pragmatic shipping with good long-term architecture.
- Autonomy & Communication: Comfortable navigating ambiguity, defining requirements collaboratively, and communicating technical discussions through clear documentation.
- Commitment to Growth: Growth mindset with continuous focus on learning and professional development.

## Preferred Qualifications

- Background provisioning or managing research computing environments (Kubernetes, SLURM, or HPC clusters)
- Experience with GPU virtualization technologies (SR-IOV, NVIDIA vGPU) and multi-tenant GPU sharing
- Background in container orchestration platforms with custom scheduling or resource management
- Knowledge of high-performance networking for GPU communication (InfiniBand, RDMA, NVLink, NVSwitch)
- Familiarity with AI/ML training frameworks (PyTorch, TensorFlow) and their infrastructure requirements
- Understanding of distributed training patterns and multi-node GPU coordination
- Experience building infrastructure for research institutions,labs, or technical computing environments
- Background in financial services or other regulated industry infrastructure is a plus

## Key Technologies

- Go, C/C++, Python, KVM, Docker, Kubernetes,, NVIDIA GPUDirect, SR-IOV, NVIDIA vGPU, CUDA, InfiniBand, RDMA, Terraform, FastAPI, gRPC, Linux systems programming

## Why Moonlite

- Build Next-Generation Infrastructure: Your work will create the platform foundation that enables financial institutions to harness AI capabilities previously impossible with traditional infrastructure.
- Hands-On Ownership: As an early engineer, you’ll have end-to-end ownership of projects and the autonomy to influence our product and technology direction.
- Shape Industry Standards: Contribute to defining how enterprise AI infrastructure should work for the most demanding regulated environments.
- Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving.
- Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space.

We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together.

#li-remote

## About Moonlite

## Company Overview
- **One-liner**: Moonlite is a family-owned barbecue restaurant in Owensboro, Kentucky, that has been serving slow-cooked, hickory-smoked meats since 1963, and is also the name of a separate high-performance AI infrastructure company.
- **Entity Type**: Private (Restaurant – Family-Owned; AI Infrastructure – Venture-Backed)
- **Headquarters**: 2840 West Parrish Avenue, Owensboro, Kentucky, USA
- **Founded**: 1963 (restaurant); AI infrastructure company founded separately
- **Founders**: Hugh "Pappy" Bosley and Catherine Bosley (restaurant); AI infrastructure founders not named in available search results

## Core Business
- Primary industry/industries: Food & Beverage (Barbecue Restaurant, Catering, Wholesale)
- Target customers: B2C (dine-in, carryout); B2B (catering, wholesale distribution)
- Mission or purpose statement: "To carry on the tradition of slow-cooked, hickory-smoked excellence" as a family business.

## Products & Services
- **Moonlite Bar-B-Q Inn (Restaurant)**: Full-service restaurant with 350 seats, serving mutton, ribs, chicken, and other barbecue meats cooked over hickory fires. Offers dine-in, carryout, and catering.
- **Catering Department**: Capable of serving 15 to 15,000 people, with notable events including the annual Toyota company picnic (nearly 15,000 guests).
- **Wholesale Division**: Distributes barbecue and related products through distributors in a four-state area.
- **U.S.D.A. Inspected Processing Plant**: Produces and packages meats for wholesale and retail.
- **Moonlite AI (Separate Entity)**: High-performance AI infrastructure platform. Provides enterprise-grade compute, networking, and storage for AI workloads, with SOC 2, ISO 27001, and ISO 42001 certifications. Offers roles in software engineering and site reliability.

## Market Standing
- **Valuation/Market Cap**: Not publicly available (private, family-owned restaurant)
- **Key Metric**: Serves over 350,000 meals per year; staff of over 120 employees; largest mutton distributor in the country, serving over 10,000 pounds of mutton per week.
- **Notable Investors/Partners**: Not publicly available (family-owned)
- **Growth Signals**: Third and fourth generations of the Bosley family now operate the business; awarded "Best Barbecue in Kentucky" by Kentucky Monthly and Kentucky Living readers. Remains a pillar of the Owensboro community.

## Competitive Advantages
- **Heritage & Authenticity**: Over 50 years of family tradition and a distinctive hickory-smoking process that takes two years (4,200 hours) to train a pitmaster.
- **Scale & Reputation**: The largest mutton distributor in the country, serving a massive annual volume and capable of catering to 15,000-person events.
- **Community & Culture**: Deep ties to Owensboro, Kentucky, supporting local charities and recognized as a "Kentucky legend."

## Strategic Focus
- Continuing the family tradition of slow-cooked, hickory-smoked barbecue.
- Expanding catering and wholesale operations.
- Maintaining high quality and consistency in preparation (12-hour slow cook over hand-built hickory fires).

## Why Work Here
- **Family-Oriented Culture**: Built on hard work, dedication, and family values with a close-knit team of over 120 members.
- **Stability & Legacy**: A long-standing, successful family business with multi-generational ownership.
- **Variety of Roles**: Opportunities in kitchen/prep, pit cooking, counter service, hosting, cashiering, buffet, server, catering, and dishwashing.
- **Location**: Owensboro, Kentucky; on-site roles. No remote or hybrid options indicated.
- **Perks**: Part of a well-respected local institution; community involvement; potential for growth within the expanding catering and wholesale operations.

## Sources
1. [moonlite.com/career](https://moonlite.com/career/) – Job application and company description
2. [moonlite.com/about-us](https://moonlite.com/about-us/) – Company history and founding story
3. [moonlite.com/media-room](https://moonlite.com/media-room/) – Media facts, history timeline, catering highlights
4. [moonlite.ai](https://www.moonlite.ai/) – Separate AI infrastructure company website (note: this is a different entity)

## Other roles at Moonlite

- [Senior Software Engineer, Network Platform](https://feeny.ai/job/senior-software-engineer-network-platform-moonlite-chicago-xfze3h9cfcqn) — Chicago, IL
- [Sr. Site Reliability Engineer (SRE)](https://feeny.ai/job/sr-site-reliability-engineer-sre-moonlite-chicago-szpan0bxmm1m) — Chicago, IL
- [Senior Software Engineer, Platform Infrastructure](https://feeny.ai/job/senior-software-engineer-platform-infrastructure-moonlite-chicago-yv59hhwwtazr) — Chicago, IL
- [Senior Software Engineer, Compute Platform](https://feeny.ai/job/senior-software-engineer-compute-platform-coinbase-united-states-pr77chqagzgf) — United States