AI Platform Engineer

AI Platform Engineer - Trootech While sharing the profile of your resource, share the details below, too, along with the LinkedIn ID
Experience Required - 8-10 Years
Timezone: 1:30 PM to 9:30 PM IST
Budget - 1.3 LPM
Work Mode: Remote

Job Description

The role will require close collaboration across AI, software, cloud, and platform engineering disciplines. It therefore requires a strong understanding of how these areas come together to enable the delivery and operation of enterprise AI solutions.

Duties and Responsibilities

Reporting to a Senior Specialist in the client s IT division, the consultant will provide the technical expertise to address the following tasks:

Contribute to the design, implementation, and maintenance of shared infrastructure and platform capabilities supporting the deployment and operation of AI models, services, and applications.

Collaborate with technical colleagues to facilitate the implementation of infrastructure, platform and deployment workstreams supporting AI applications, APIs and other enterprise platforms

Configure and maintain API management and gateway services, including Azure API Management (APIM), to support secure and scalable access to AI models and services across on-premises, cloud and external provider environments

Develop and maintain CI/CD pipelines and infrastructure automation for AI platform components and model deployments, in accordance with established enterprise standards.

Develop Terraform-based infrastructure-as-code deployments to provision, configure and maintain AI platform components and related cloud services.

Support the integration of enterprise AI services with applications, APIs and other enterprise systems, providing implementation support as required

Produce and maintain appropriate technical documentation, deployment procedures and operational guidance for AI platform components and services

Any other support duties as required

Professional Requirements

At least 8-10 years of professional work experience.

Hands-on experience supporting the deployment and operation of scalable, reliable, and secure applications, AI services, and enterprise platforms across cloud, on-premises, and hybrid environments

Hands-on Experience working across AI, Terraform (IaC), software development, cloud, and platform engineering teams, with the ability to translate business and technical requirements into practical implementation solutions

Solid understanding of the software development lifecycle, modern software engineering practices, and enterprise-grade software deployment and operations

Problem Solver: able to critically analyse problems, explore different solutions, consider various options, and effectively complete tasks

Team Worker: able to consult and deal effectively with all levels of technical and non-technical stakeholders and partners in the organization, establishing working relations of openness and trust in a multicultural setting

Proactive Planner: able to prioritize and organize work for effective resolutions of problems whilst staying ahead of potential issues

Effective Communicator: ability to communicate effectively to understand and explain technical and non-technical matters to stakeholders and partners in the organization

Qualification and Experience

University degree in Computer Science, Computer Engineering, Software Engineering, Systems Engineering, or related discipline

Technical Requirements

Strong hands-on experience with Microsoft Azure, including the deployment, configuration, integration, and operation of cloud-based applications, services, and platform components

Strong experience with API management and gateway technologies, preferably Azure API Management (APIM), including configuration, routing, load balancing, failover, security, and integration of backend services.
Strong experience with containerized architectures and deployments using Docker and Kubernetes, including the deployment, configuration and scaling of services in Kubernetes environments
Experience with CI/CD pipelines, infrastructure automation, version control, DevSecOps and modern software engineering practices
Experience with infrastructure-as-code and automated provisioning technologies, such as Terraform, Bicep or equivalent tools
Strong understanding of Artificial Intelligence and Machine Learning models, services and architectures, including Generative AI, Large Language Models and other AI model types, with experience in their deployment, integration and operationalization
Experience with AI model serving and inference architectures, including the deployment of model-serving workloads in Kubernetes environments and familiarity with technologies such as vLLM, NVIDIA NIM or equivalent frameworks
Good working knowledge of Python, with experience in automation, API integration and AI-related workloads
Good knowledge of API design, networking, authentication and authorization, and integration of enterprise services.
Languages
Excellent written and verbal communication skills in English is essential. Knowledge of additional languages is an advantage.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.