Senior AI Infra Engineer for Scalable Enterprise Platforms

Seekr; Austin (TX); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Equity Ownership

Unlimited PTO and holidays

Hybrid work environment (Reston, VA &\

401(k) with company match

Comprehensive health & wellness

Job summary

Seekr is building the infrastructure that powers the next generation of enterprise AI, seeking a Senior AI Infrastructure Engineer to design, build, and operate platforms for 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 from

Qualifications

• 5–8 years of professional software engineering experience building distributed systems, cloud infrastructure, or large-scale platform services.
• Strong production ML infra experience, executes complex work independently, owns significant components
• 4 year or higher degree or additional relevant experience, in addition to years of work experience
• Demonstrated success designing and operating production Kubernetes environments supporting cloud-native applications and distributed services.
• Strong software engineering skills using Python and one or more modern programming languages such as Go, Rust, or C++.
• Proven ability to design, build, and operate production AI or machine learning infrastructure.
• Expertise developing and optimizing large-scale AI inference platforms, including GPU utilization, distributed inference, batching, caching, quantization, and accelerator performance.

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.

Skills

Distributed systems

Kubernetes

GPU infrastructure

Python

Go/Rust/C++

ML infra

Cloud platforms

Mentoring

System design leadership

Education

Bachelor's degree or higher in CS/Engineering

Tools

Kubernetes

Prometheus

Grafana

OpenTelemetry

Docker

Job description

Seekr is building the infrastructure that powers the next generation of enterprise AI, seeking a Senior AI Infrastructure Engineer to design, build, and operate platforms for 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 from