Principal AI Platform Engineer; AI Infrastructure & Platform Engineering

Location: Seattle, WA (Hybrid | 2–3 days/week)

Compensation: $280,000–$375,000 Base + Bonus + Equity

We're partnering with an established Enterprise AI & Technology Consulting organization, helping Fortune 500 enterprises and high-growth technology companies design, build, and scale production AI platforms.

As demand for enterprise AI continues to accelerate, they're expanding their AI Platform Engineering practice and are looking to hire a Principal AI Platform Engineer to lead the architecture and delivery of cloud-native AI platforms supporting Generative AI, Agentic AI, and Machine Learning initiatives across multiple enterprise clients.

This is a highly technical leadership role combining platform architecture, hands‑on engineering, and client advisory. You'll work alongside engineering leaders, architects, and executive stakeholders to solve complex infrastructure challenges while defining scalable AI platforms that enable organizations to build, deploy, and operate AI securely at enterprise scale.

As the Principal AI Platform Engineer, you'll serve as the technical authority across multiple enterprise engagements, owning the design and evolution of production AI platforms from architecture through implementation.

You'll be responsible for:

• Designing scalable AI platform architectures supporting enterprise AI initiatives.
• Building reusable cloud-native platform capabilities that enable engineering teams to rapidly deploy AI applications.
• Establishing platform standards, reference architectures, and engineering best practices.
• Driving AI platform modernization across Kubernetes, cloud infrastructure, automation, and AI services.
• Providing technical leadership throughout architecture, implementation, and platform adoption.
• Mentoring senior engineers while helping shape the long‑term technical direction of the AI Platform practice.

Lead the design and evolution of enterprise AI platforms focused on scalability, automation, and developer enablement by building:

• Internal Developer Platforms (IDPs)
• Self‑service AI infrastructure
• Platform observability and governance

Architect production AI environments supporting:

• Enterprise LLM applications
• Retrieval‑Augmented Generation (RAG)
• Agentic AI solutions
• GPU‑accelerated AI workloads
• Distributed AI infrastructure
• Vector search platforms

Experience with technologies such as Ray, KServe, Kubeflow, MLflow, vLLM, NVIDIA Triton, Lang Graph, MCP, or comparable AI platform technologies is highly desirable.

As the technical lead across enterprise engagements, you'll:

• Translate business objectives into scalable AI platform architectures.
• Lead architecture and technical discovery workshops.
• Recommend cloud and platform modernization strategies.
• Define AI platform roadmaps.

This role typically involves 20–30% client interaction
, with the remainder focused on architecture, platform engineering, and technical leadership.

• 10+ years of experience across Platform Engineering, Infrastructure Engineering, Cloud Engineering, or Software Engineering.
• 5+ years designing enterprise‑scale cloud or platform architectures.
• Experience operating as a Principal Engineer, Staff Engineer, Platform Architect, or Technical Lead.
• Proven success in designing and delivering production AI platform initiatives.

Strong experience building modern cloud‑native platforms utilizing:

• Docker
• Terraform
• Git Ops
• Infrastructure Automation
• Internal Developer Platforms
• Cloud‑native architecture

Deep expertise with one or more:

• AWS

• Experience supporting production AI environments involving GPU‑accelerated workloads, distributed AI systems, vector search, AI platform security, production monitoring and observability for AI workloads.

We're looking for someone who enjoys solving complex technical problems while helping engineering organizations scale.

You’ll be comfortable:

• Influencing technical direction across multiple engineering teams.
• Mentoring senior engineers.
• Navigating ambiguous technical challenges.
• Communicating effectively with engineering leadership and executive stakeholders.
• Balancing strategic thinking with hands‑on technical contribution.

This is an opportunity to help shape how leading organizations adopt AI at scale.

Rather than supporting a single product, you’ll partner with organizations across industries to design scalable AI platforms, modernize cloud infrastructure, and enable engineering teams to deliver production AI applications securely and efficiently.