Principal GenAI Platform Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal GenAI Platform Engineer in the United States.

This role sits at the core of a rapidly evolving GenAI platform, focused on building the foundational infrastructure that powers safe, scalable, and production-ready generative AI systems. You will design and develop the critical backend layers that enable AI models to integrate seamlessly into enterprise products and agent-based workflows. The position requires deep expertise in AI infrastructure, cloud-native systems, and distributed architectures to support high-performance LLM workloads. You will collaborate closely with product, engineering, and data teams to ensure GenAI capabilities are reliably delivered across multiple applications. This is a highly technical, hands-on leadership role with strong influence on platform architecture, scalability, and security. It is ideal for an engineer passionate about building robust AI systems that operate at enterprise scale.

In this role, you will architect and build the core infrastructure powering GenAI capabilities, ensuring scalability, security, observability, and seamless integration with downstream AI-driven applications.

• Design, build, and maintain core GenAI platform infrastructure, including model gateways, prompt/versioning systems, vector databases, and LLM evaluation tools
• Develop secure authentication and authorization frameworks embedded directly into AI platform services
• Implement observability, monitoring, and logging systems for GenAI workloads using modern telemetry and performance tools
• Collaborate with product and engineering teams to integrate GenAI infrastructure into agent frameworks and enterprise applications
• Optimize platform performance for scalability, high availability, and cost efficiency across production AI workloads
• Build and maintain CI/CD pipelines and automation workflows for AI model deployment and platform operations
• Support the design and evolution of AI infrastructure components that enable reliable LLM inference and orchestration
• Ensure platform reliability and resilience through performance tuning, system design, and operational best practices
• Contribute to architectural decisions for enterprise-grade GenAI systems and infrastructure standards

Requirements:

This role requires deep technical expertise in AI infrastructure, cloud-native systems, and scalable platform engineering, with a strong focus on production-grade GenAI environments.

• Extensive experience building and maintaining AI platform infrastructure, Kubernetes environments, and containerized systems
• Strong background in observability and monitoring frameworks such as OpenTelemetry or MLflow
• Experience working with AI infrastructure components including vector databases, prompt/versioning stores, and LLM tooling
• Familiarity with LLM inference frameworks such as vLLM, SGLang, or similar technologies
• Strong knowledge of authentication and authorization mechanisms in distributed systems
• Experience building CI/CD pipelines and automating deployment workflows for AI/ML systems
• Solid understanding of cloud architecture, scalability patterns, and high-availability systems
• Experience integrating AI systems into production applications and agent-based workflows
• Strong problem-solving skills with the ability to design complex distributed systems
• Excellent collaboration skills for working across product, engineering, and platform teams

Benefits:

• Competitive base salary range: $179,000 – $199,000 annually
• Performance-based bonus and comprehensive benefits package
• Remote-friendly work environment (#LI-remote)
• Opportunity to build cutting-edge GenAI platform infrastructure at enterprise scale
• Strong focus on technical innovation and modern AI system architecture
• Collaborative engineering culture working closely with product and AI teams
• Exposure to advanced LLM technologies and production-grade AI workloads
• Career growth in a high-impact, rapidly evolving AI engineering domain