[Hiring] Forward Deployed AI Engineer @Red River

Role Description

The Red Hat AI Customer Adoption and Innovation (CAI) team is looking for a North-America based 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, deploy, and optimize complex AI inference solutions, while simultaneously capturing those lessons to enable our wider field teams.

This position can be remote, but the candidate has to be located in North America, United States preferred, and willing to travel as required, up to 20% of the time.

What you will do

• Lead Lighthouse Implementations: Lead the technical delivery for critical, high-profile customer Proofs of Concept (POCs) and production pilots.
• Optimization & Architecture: Provide expert advice on inference sizing, configuration, and resource management.
• Field Enablement & Asset Creation: Enable our field teams by turning lessons from customer engagements into reusable assets.
• Stakeholder Communication: Translate technical metrics into business value.
• Product Feedback Loop: Act as a liaison between the customer and the Product and Engineering teams.

What you will bring

• Consulting & Architecture Experience: Proven experience in a technical consulting, professional services, or solutions architect role (10+ years).
• Deep OpenShift or Kubernetes Expertise: Extensive hands-on experience with OpenShift or Kubernetes (5+ years).
• Performance & Optimization Mindset: Background or strong interest in system performance.
• Inference background: Familiarity with inference technologies such as Kserve, vLLM, and potentially llm-d (2+ years).
• Functional Python Skills: 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.

Preferred Experience (Bonus Points)

• 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.

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!