AI Platform Engineer

Skillsearch Limited; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Skillsearch Limited is seeking an AI Platform Engineer to design, deploy and operate the infrastructure layer enabling enterprise AI applications, APIs and services. You will collaborate with AI, software, cloud and platform teams to deploy, scale and operate modern AI workloads across cloud, hybrid and on‑prem environments.

The role covers API management, IaC, CI/CD, DevOps and model deployment operations, with a focus on secure, scalable platform capabilities and governance across diverse

Qualifications

• Minimum 4 years' professional experience in platform engineering, cloud engineering, DevOps, infrastructure or related disciplines.
• Experience deploying and operating enterprise applications and services across cloud and hybrid environments.
• Hands-on experience working across software, cloud, AI and platform engineering teams.
• Experience supporting production environments and business-critical systems.
• Strong understanding of software delivery, operational support and infrastructure management.

Responsibilities

• Contribute to the design, implementation and maintenance of shared AI infrastructure and platform services.
• Support the deployment and operation of AI models, applications and enterprise AI services.
• Build scalable, secure and reliable platform capabilities across cloud, hybrid and on-premises environments.
• Collaborate with engineering teams to deliver infrastructure and deployment workstreams.
• Configure and maintain API gateway and API management solutions.
• Support secure and scalable access to AI services and enterprise applications.
• Design and manage API integrations across cloud, on-premises and third-party environments.
• Implement routing, security, authentication and service governance controls.
• Develop and maintain Infrastructure-as-Code solutions using Terraform and related technologies.
• Automate cloud provisioning, deployment and environment management.
• Build reusable infrastructure modules and deployment patterns.
• Support enterprise infrastructure standardisation efforts.
• Develop and maintain CI/CD pipelines supporting AI platform services and model deployments.
• Implement automation for build, deployment and operational workflows.
• Improve software delivery processes and deployment consistency.
• Support DevSecOps and modern engineering practices.
• Support deployment, serving and operationalisation of AI and machine learning workloads
• Assist with AI model integration into enterprise platforms and applications.
• Support model serving infrastructure and inference platforms.
• Monitor platform performance, scalability and reliability.
• Produce and maintain technical documentation.
• Develop deployment guides, operational procedures and support materials.
• Support knowledge sharing and best-practice adoption across engineering teams.
• Contribute to ongoing platform improvement initiatives.

Skills

Azure

Kubernetes

Docker

Terraform

CI/CD

Python

API

DevSecOps

Model serving

Automation

APIs

Education

Degree in Computer Science or related

Tools

Terraform

Bicep

Kubernetes

Docker

Azure

Job description

As an AI Platform Engineer, you will contribute to the design, deployment and operation of the infrastructure layer that enables enterprise AI applications, APIs and services.

Working closely with AI, software, cloud and platform engineering teams, you will help establish the shared capabilities required to deploy, scale and operate modern AI workloads. This includes cloud infrastructure, API management, automation, CI/CD, Kubernetes platforms and infrastructure-as-code solutions.

This is an ideal opportunity for someone who enjoys solving complex technical challenges while working across multiple engineering disciplines.

Key Responsibilites

AI Platform & Infrastructure Engineering

• Contribute to the design, implementation and maintenance of shared AI infrastructure and platform services.
• Support the deployment and operation of AI models, applications and enterprise AI services.
• Build scalable, secure and reliable platform capabilities across cloud, hybrid and on-premises environments.
• Collaborate with engineering teams to deliver infrastructure and deployment workstreams.

API Management & Integration

• Configure and maintain API gateway and API management solutions.
• Support secure and scalable access to AI services and enterprise applications.
• Design and manage API integrations across cloud, on-premises and third-party environments.
• Implement routing, security, authentication and service governance controls.

Infrastructure as Code & Automation

• Develop and maintain Infrastructure-as-Code solutions using Terraform and related technologies.
• Automate cloud provisioning, deployment and environment management.
• Build reusable infrastructure modules and deployment patterns.
• Support enterprise infrastructure standardisation efforts.

DevOps & CI/CD

• Develop and maintain CI/CD pipelines supporting AI platform services and model deployments.
• Implement automation for build, deployment and operational workflows.
• Improve software delivery processes and deployment consistency.
• Support DevSecOps and modern engineering practices.

AI Deployment & Operations

• Support deployment, serving and operationalisation of AI and machine learning workloads
• Assist with AI model integration into enterprise platforms and applications.
• Support model serving infrastructure and inference platforms.
• Monitor platform performance, scalability and reliability.

Documentation & Operational Readiness

• Produce and maintain technical documentation.
• Develop deployment guides, operational procedures and support materials.
• Support knowledge sharing and best-practice adoption across engineering teams.
• Contribute to ongoing platform improvement initiatives.

What We're Looking For

Experience

• Minimum 4 years' professional experience in platform engineering, cloud engineering, DevOps, infrastructure or related disciplines.
• Experience deploying and operating enterprise applications and services across cloud and hybrid environments.
• Hands-on experience working across software, cloud, AI and platform engineering teams.
• Experience supporting production environments and business-critical systems.
• Strong understanding of software delivery, operational support and infrastructure management.

Technical Skills

Cloud & Platform Engineering

• Strong hands-on experience with Microsoft Azure.
• Experience deploying, managing and integrating cloud-based applications and services.
• Understanding of hybrid cloud architectures and enterprise environments.

API Management

• Strong experience with API gateways and API management platforms.
• Experience with Azure API Management (APIM) highly desirable.
• Understanding of:
  • Routing
  • Load balancing
  • Failover
  • Authentication
  • Authorization
  • Service integration

Containers & Kubernetes

• Strong experience with Docker and containerised environments.
• Experience deploying and operating Kubernetes workloads.
• Understanding of scaling, monitoring and service management within Kubernetes environments.

Infrastructure As Code & Automation

• Strong experience with Terraform.
• Experience with Bicep or other Infrastructure-as-Code tools is beneficial.
• Experience designing reusable automation and provisioning frameworks.

DevOps & CI/CD

• Experience implementing CI/CD pipelines.
• Understanding of:
  • Infrastructure automation
  • Version control
  • DevSecOps
  • Modern software engineering practices
• Experience supporting deployment automation in enterprise environments.

AI & Machine Learning Platforms

• Understanding of:
  • Artificial Intelligence
  • Machine Learning
  • Generative AI
  • Large Language Models (LLMs)
• Experience deploying, integrating or operating AI services.
• Experience supporting AI workloads in production environments.
• Knowledge of model serving and inference architectures.

Programming

• Good Python development skills.
• Experience with:
  • Automation
  • API integrations
  • AI-related workloads
• Understanding of application integration patterns and enterprise systems.

Desirable Experience

• Kubernetes-based model serving
• vLLM
• NVIDIA NIM
• AI inference platforms
• Enterprise AI operations
• High-availability cloud architectures
• Multi-cloud deployments
• Security and governance frameworks

Personal Qualities

• Strong problem-solving abilities.
• Excellent analytical and troubleshooting skills.
• Proactive and highly organised.
• Comfortable working independently and as part of a multidisciplinary team.
• Strong communication skills with both technical and non-technical stakeholders.
• Collaborative approach in international and multicultural environments.
• Able to prioritise effectively and manage competing demands.

Qualifications

• Degree in Computer Science, Software Engineering, Computer Engineering, Systems Engineering or a related discipline.
• Relevant Azure, Kubernetes, Terraform or cloud certifications are advantageous.

Languages

• Excellent written and spoken English.
• Additional languages such as Spanish, French, Portuguese or Arabic would be beneficial.

Success In This Role

• Enterprise AI platforms are secure, scalable and operationally reliable.
• Infrastructure deployments are automated, repeatable and maintainable.
• AI services are successfully integrated into enterprise applications and platforms.
• CI/CD and infrastructure automation improve engineering efficiency.
• Platform reliability, observability and operational readiness continuously improve.
• Engineering teams are supported by strong shared platform capabilities and modern development processes.

Why Join?

• Work on enterprise-scale AI initiatives.
• Operate at the intersection of AI, cloud and platform engineering.
• Help shape next-generation AI infrastructure and services.
• Collaborate with multidisciplinary engineering teams.
• Significant opportunity for technical growth and impact.
• Contribute to building secure, scalable and production-ready AI platforms.

If you're passionate about cloud infrastructure, automation and enabling enterprise AI at scale, we'd love to hear from you.