Forward Deployed AI Engineer, Customer Adoption and Innovation

About the job

The Red Hat AI Customer Adoption and Innovation (CAI) team is looking for a Forward Deployed AI Engineer to join our rapidly growing AI Business Unit.

As inference technologies become more mainstream, our customers are seeking deep expertise in optimization, scalability, and production readiness. In this role, you will act as a bridge between engineering and the customer's environment. You will be deployed to support lighthouse customer engagements, ensuring that Red Hat AI inference products are successfully implemented, tuned, and optimized to meet specific business requirements.

We are looking for a hands‑on practitioner who understands that technical implementation must serve a business constraint—whether that’s cost, latency, or throughput. You will work directly with customers to design and deploy and optimize complex AI inference solutions, while simultaneously capturing those lessons to enable our wider field teams.

While you will have the support of the wider CAI team to upskill on specific AI technologies, you must bring a strong consulting mindset and deep technical expertise in Open Shift or Kubernetes platform engineering.

• Lead Lighthouse Implementations: Lead the technical delivery for critical, high‑profile customer Proofs of Concept (POCs) and production pilots. You will be the primary technical expert hands‑on with the customer, helping them navigate the complexities of LLM inference in their specific clusters.
• Optimization & Architecture: Provide expert advice on inference sizing, configuration, and resource management. You will guide customers on how to best configure their Open Shift environments to support computationally intensive AI workloads.
• Field Enablement & Asset Creation: Enable our field teams by turning lessons from customer engagements into reusable assets. You will develop reference architectures, field manuals, and validated patterns that allow other AI specialists to execute similar engagements independently.
• Stakeholder Communication: Translate technical metrics into business value. You will be expected to communicate effectively with both technical teams (Dev Ops, SREs) and business stakeholders to justify architecture decisions.
• Product Feedback Loop: Act as a liaison between the customer and the Product and Engineering teams. You will ensure that real‑world feedback regarding platform performance and usability is properly prioritized in the product roadmap.

• Consulting & Architecture
  
  Experience:
  
  Proven experience in a technical consulting, professional services, or solutions architect role. You are comfortable leading the delivery of complex technical solutions and managing customer expectations in a post‑sales or implementation environment.
• Deep Open Shift or Kubernetes Expertise: You possess extensive hands‑on experience with Open Shift or Kubernetes. You deeply understand how to deploy, scale, and manage complex workloads, operator life cycles, and resource quotas in a containerized environment.
• Performance & Optimization Mindset: You have a background or strong interest in system performance. You understand concepts regarding latency, throughput, and efficient resource utilization.
• Inference background: You should already have familiarity with inference technologies such as Kserve, vLLM, and potentially llm‑d.
• Functional Python
  
  Skills:
  
  You are capable of reading and writing Python code to script automation or interact with necessary libraries.
• Communication
  
  Skills:
  
  Excellent written and verbal communication skills in English. You can confidently present to audiences ranging from operations teams to business leadership.

• Familiarity with the AI Stack: Experience with tools like llm‑compressor, guidellm, etc.
• Networking Knowledge: Understanding of networking concepts (L7/Gateway API) or high‑performance computing networking.
• Model Tuning
  
  Experience:
  
  Exposure to post‑training techniques such as knowledge distillation, LoRA/QLoRA, or quantization.

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The salary range for this position is $ - $. Actual offer will be based on your qualifications.

Red Hat determines…