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Forward Deployed Engineer, AI Inference (vLLM and Kubernetes)
full-timeUnited States$193k - $318k

Summary

Location

United States

Salary

$193k - $318k

Type

full-time

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About this role

The vLLM and LLM-D Engineering team at Red Hat is looking for a customer obsessed developer to join our team as a Forward Deployed Engineer. In this role, you will not just build software; you will be the bridge between our cutting-edge inference platform (LLM-D, and vLLM) and our customers' most critical production environments.

You will interface directly with the engineering teams at our customer to deploy, optimize, and scale distributed Large Language Model (LLM) inference systems. You will solve "last mile" infrastructure challenges that defy off-the-shelf solutions, ensuring that massive models run with low latency and high throughput on complex Kubernetes clusters. This is not a sales engineering role, you will be part of the core vLLM and LLM-D engineering team.

What You Will Do

  • Orchestrate Distributed Inference: Deploy and configure LLM-D and vLLM on Kubernetes clusters. You will set up and configure advanced deployment like disaggregated serving, KV-cache aware routing, KV Cache offloading etc to maximize hardware utilization.

  • Optimize for Production: Go beyond standard deployments by running performance benchmarks, tuning vLLM parameters, and configuring intelligent inference routing policies to meet SLOs for latency and throughput. You care about Time Per Output Token (TPOT), GPU utilization, GPU networking optimizations, and Kubernetes scheduler efficiency.

  • Code Side-by-Side: Work directly with customer engineers to write production-quality code (Python/Go/YAML) that integrates our inference engine into their existing Kubernetes ecosystem.

  • Solve the "Unsolvable": Debug complex interaction effects between specific model architectures (e.g., MoE, large context windows), hardware accelerators (NVIDIA GPUs, AMD GPUs, TPUs), and Kubernetes networking (Envoy/ISTIO).

  • Feedback Loop: Act as the "Customer Zero" for our core engineering teams. You will channel field learnings back to product development, influencing the roadmap for LLM-D and vLLM features.

  • Travel only as needed to customers to present, demo, or help execute proof-of-concepts.  

What You Will Bring

  • 8+ Years of Engineering Experience: You have a decade-long track record in Backend Systems, SRE, or Infrastructure Engineering.

  • Customer Fluency: You speak both "Systems Engineering" and "Business Value".

  • Bias for Action: You prefer rapid prototyping and iteration over theoretical perfection. You are comfortable operating in ambiguity and taking ownership of the outcome.

  • Deep Kubernetes Expertise: You are fluent in K8s primitives, from defining custom resources (CRDs, Operators, Controllers) to configuring modern ingress via the Gateway API. You have deep experience with stateful workloads and high-performance networking, including the ability to tune scheduler logic (affinity/tolerations) for GPU workloads and troubleshoot complex CNI failures.

  • AI Inference Proficiency: You understand how a LLM forward pass works. You know what KV Caching is, why prefill/decode disaggregation matters, why context length impacts performance, and how continuous batching works in vLLM.

  • Systems Programming: Proficiency in Python (for model interfaces) and Go (for Kubernetes controllers/scheduler logic).

  • Infrastructure as Code: Experience with Helm, Terraform, or similar tools for reproducible deployments.

  • Cloud & GPU Hardware Fluency: You are comfortable spinning up clusters and deploying LLMs on bare-metal and hyperscaler Kubernetes clusters.

Following is considered a plus

  • Experience contributing to open-source AI infrastructure projects (e.g., KServe, vLLM, Kubernetes).

  • Knowledge of Envoy Proxy or Inference Gateway (IGW).

  • Familiarity with model optimization techniques like Quantization (AWQ, GPTQ) and Speculative Decoding.

#AI-HIRING

#LI-MD2

The salary range for this position is $193,390.00 - $318,980.00. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience. 

About Red Hat

Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Benefits
●    Comprehensive medical, dental, and vision coverage
●    Flexible Spending Account - healthcare and dependent care
●    Health Savings Account - high deductible medical plan
●    Retirement 401(k) with employer match
●    Paid time off and holidays
●    Paid parental leave plans for all new parents
●    Leave benefits including disability, paid family medical leave, and paid military leave
●    Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more! 

Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States. 

Inclusion at Red Hat
Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.


Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.

Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email [email protected]. General inquiries, such as those regarding the status of a job application, will not receive a reply. 

Other facts

Tech stack
Kubernetes,AI Inference,Python,Go,Infrastructure as Code,Cloud,GPU Hardware,Backend Systems,SRE,Distributed Systems,Performance Optimization,Debugging,Customer Engagement,Open Source,Model Optimization,Networking

About Red River

Red River brings together the ideal combination of talent, partners and products to disrupt the status quo in technology and drive success for business and government in ways previously unattainable. Red River serves organizations well beyond traditional technology integration, bringing more than 20 years of experience and mission-critical expertise in security, networking, analytics, collaboration, mobility and cloud solutions. Learn more at redriver.com.

Team size: 501-1,000 employees
LinkedIn: Visit
Industry: IT Services and IT Consulting
Founding Year: 1995

What you'll do

  • You will deploy and configure LLM-D and vLLM on Kubernetes clusters, optimizing for production and solving complex infrastructure challenges. Additionally, you will work directly with customer engineers to integrate the inference engine into their existing systems.

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Frequently Asked Questions

What does Red River pay for a Forward Deployed Engineer, AI Inference (vLLM and Kubernetes)?

Red River offers a competitive compensation package for the Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) role. The salary range is USD 193k - 319k per year. Apply through Clera to learn more about the full compensation details.

What does a Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) do at Red River?

As a Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) at Red River, you will: you will deploy and configure LLM-D and vLLM on Kubernetes clusters, optimizing for production and solving complex infrastructure challenges. Additionally, you will work directly with customer engineers to integrate the inference engine into their existing systems..

Why join Red River as a Forward Deployed Engineer, AI Inference (vLLM and Kubernetes)?

Red River is a leading IT Services and IT Consulting company. The Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) role offers competitive compensation.

Is the Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) position at Red River remote?

The Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) position at Red River is based in United States, United States. Contact the company through Clera for specific work arrangement details.

How do I apply for the Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) position at Red River?

You can apply for the Forward Deployed Engineer, AI Inference (vLLM and Kubernetes) position at Red River directly through Clera. Click the "Apply Now" button above to start your application. Clera's AI-powered platform will help match your profile with this opportunity and guide you through the application process. You can also learn more about Red River on their website.