AI Infrastructure Engineer

Seekr is building the infrastructure that powers the next generation of enterprise AI. As a Staff AI Infrastructure Engineer, you will design, build, and operate the platforms that enable large-scale training, serving, evaluation, and deployment of foundation models and autonomous AI agents.

You will work across distributed systems, Kubernetes, GPU infrastructure, high-performance inference, and enterprise AI platforms to build secure, scalable, and highly reliable systems capable of serving workloads ranging from edge AI deployments to trillion-parameter foundation models.

This role requires deep expertise in distributed systems, cloud-native infrastructure, AI platform engineering, and production software development. You will collaborate with research scientists, software engineers, product teams, and infrastructure engineers to define the architecture and technical direction of Seekr’s AI platform.

Duties and Responsibilities

• Design, develop, deploy, and maintain production AI infrastructure supporting model training, fine-tuning, inference, evaluation, and agentic AI workloads.
• Design and operate scalable Kubernetes-based infrastructure supporting GPU-accelerated workloads across cloud, on-premises, hybrid, and edge environments.
• Architect and optimize high-performance inference platforms capable of serving models ranging from resource-constrained edge deployments to trillion-parameter foundation models, with a focus on latency, throughput, scalability, reliability, and cost efficiency.
• Build and maintain distributed systems that enable reliable scheduling, orchestration, deployment, monitoring, and lifecycle management of AI workloads.
• Develop enterprise platforms supporting autonomous and multi-agent AI systems, including secure tool execution, orchestration, memory, evaluation, governance, and observability.
• Design, implement, and automate AI infrastructure using Infrastructure-as-Code, GitOps, CI/CD pipelines, and modern software engineering practices.
• Evaluate and integrate emerging AI infrastructure technologies, model serving frameworks, hardware accelerators, and cloud-native platforms to improve platform performance, scalability, and reliability.
• Collaborate with engineering, research, product, and cross-functional teams to deliver secure, scalable, and production-ready AI platforms.
• Lead technical design discussions, perform architecture reviews, mentor engineers, and establish engineering standards and best practices across the AI Infrastructure organization.
• Participate in production support activities, including troubleshooting complex distributed systems, performance tuning, incident response, and continuous operational improvement.