Principal GenAI Platform Engineer
Indexed description
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.
Accountabilities:
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
- 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
- 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
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.
Benefits:
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