AI Infrastructure Engineer

Palona AI; New York (NY); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Competitive salary

Stock option plan

Medical, dental, vision benefits

Retirement plan

Family leave

Short/Long-term disability

Paid time off and holidays

Learning and development support

Job summary

Palona AI is seeking a cloud infrastructure engineer to design and evolve secure, scalable systems powering real-time AI services. You will work on architecture, performance, data flows, and operational readiness to support new capabilities and complex AI workloads.

You will drive reliability through SLOs, capacity planning, and incident prevention, while building deployment systems and IaC patterns across development, staging, and production.

Qualifications

• 3+ years industrial experience in relevant technical domain.
• Experience building/operating production distributed systems.
• Hands-on with a major cloud platform (AWS preferred).
• Experience with containers, IaC, CI/CD, monitoring, alerting, and production debugging.
• Ability to write reliable automation and services in Python or another modern language.
• Judgment on availability, latency, scalability, security, and cost tradeoffs.
• History of diagnosing ambiguous operational problems to durable resolution.
• Clear communication during architecture reviews, launches, and incidents.
• AI-native operating habits and curiosity about LLM- and agent-powered systems.

Responsibilities

• Design, build, and evolve secure, scalable cloud infrastructure for real-time AI services and customer-facing applications.
• Improve service reliability through clear SLOs, observability, capacity planning, failure testing, and incident prevention.
• Build deployment and release systems that are fast, repeatable, auditable, and safe.
• Own infrastructure as code, environment consistency, and reusable platform patterns across environments.
• Partner with product and AI engineers on architecture, performance, data flows, and operational readiness for new capabilities.
• Diagnose complex distributed-system failures across application, network, database, model-provider, and third-party boundaries.
• Reduce infrastructure and model-serving cost without harming user experience or velocity.
• Strengthen secrets management, access controls, backups, vulnerability management, and security foundations.
• Build internal tooling and paved paths to ship and operate services with less manual work.
• Participate in incident response and turn incidents into better systems and processes.

Skills

Distributed systems

Python automation

System reliability

Incident response

Communication

Security awareness

Cost optimization

AI-native operations

Tools

AWS

Kubernetes

Docker

Terraform

CI/CD tooling

Monitoring

Job description

Palona's AI agents operate continuously in production, handle real-time guest interactions, integrate with restaurant systems, and face sharp traffic peaks. Infrastructure is therefore part of the product: latency, reliability, deployment safety, observability, security, and cost directly shape the guest and operator experience.

What you will own:

• Design, build, and evolve secure, scalable cloud infrastructure for real-time AI services and customer-facing applications
• Improve service reliability through clear SLOs, actionable observability, capacity planning, failure testing, and pragmatic incident prevention
• Build deployment and release systems that make production changes fast, repeatable, auditable, and safe
• Own infrastructure as code, environment consistency, and reusable platform patterns across development, staging, and production
• Partner with product and AI engineers on architecture, performance, data flows, and operational readiness for new capabilities
• Diagnose complex distributed-system failures across application, network, database, model-provider, and third-party integration boundaries
• Reduce infrastructure and model-serving cost without compromising customer experience or engineering velocity
• Strengthen secrets management, access controls, backup and recovery, vulnerability management, and other practical security foundations
• Build internal tooling and paved paths that let engineers ship and operate services with less manual work
• Participate in incident response and turn incidents into better systems, automation, documentation, and engineering judgment

Requirements

• 3+ years industrial experience in relevant technical domain
• Strong software engineering fundamentals and experience building or operating production distributed systems
• Hands-on experience with a major cloud platform; AWS experience is especially relevant
• Experience with containers, infrastructure as code, CI/CD, monitoring, alerting, and production debugging
• Ability to write reliable automation and services in Python or another modern programming language
• Sound judgment around availability, latency, scalability, security, and cost tradeoffs
• A track record of taking ambiguous operational problems from diagnosis through durable resolution
• Clear communication during architecture reviews, launches, and incidents
• AI-native working habits and curiosity about the operational behavior of LLM- and agent-powered systems

Benefits

• Competitive Salary and Stock Option Plan
• Medical, dental, vision, retirement, leave, and disability benefits as applicable
• Family Leave
• Short Term & Long Term Disability
• Paid time off and company holidays
• Learning and development support