AI Infrastructure Engineering

Role & resp

• Job Description SummarySr Spec DDIT IES cloud Engineer will be responsible for designing, engineering, implementing, and operating enterprise AI infrastructure and platform capabilities that enable secure, scalable, and governed adoption of AI technologies across the enterprise.

  The role will focus on engineering enterprise AI platforms, developer environments, infrastructure, automation, and enterprise integrations across SaaS AI platforms, cloud AI services, hybrid, and on-premises environments. The role will collaborate with Enterprise Architecture, Hybrid Infrastructure, Security, Identity & Access Management, Networking, End User Computing, Operations, AI Enablement, and Business Technology teams.

• JustificationJustificationThis role will play a crucial part in engineering and operationalizing the enterprise AI infrastructure and platform capabilities required to enable secure, scalable, and governed adoption of AI technologies across the organization. As the enterprise accelerates its adoption of Generative AI, AI agents, and AI-enabled applications, there is a critical need for foundational platform services that allow business, data science, and application teams to consume AI capabilities reliably and securely.

  Our focus will be on designing, configuring, and integrating enterprise AI platforms spanning SaaS AI services (such as ChatGPT Enterprise, Claude, Gemini), cloud AI services (Azure AI Foundry, AWS Bedrock, Vertex AI), and hybrid/on-premises AI environments (Run.AI, SLURM, open-source AI platforms) — to provide the required services, developer environments, APIs, and model access patterns that enterprise teams need to build and run AI-powered solutions effectively.

Hiring Requirements

Job Details

• Job ProfileJob Profile

• Platform Services Level 4

• Job Families for Job ProfilesJob Families for Job Profiles

• Service Delivery & Operations

• Worker Sub-TypeWorker Sub-Type

• Regular

• Worker TypeWorker Type

• Employee

• Time TypeTime Type

• Full time

• Employee Contract TypeEmployee Contract Type

• Unlimited Contract

• Compensation GradeCompensation Grade

• Level 4

• Primary LocationPrimary Location

• Hyderabad (Office)

• Primary Job Posting LocationPrimary Job Posting Location

• Hyderabad (Office)

• Additional LocationsAdditional Locations(empty)

• Additional Job Posting LocationsAdditional Job Posting Locations(empty)

• Scheduled Weekly HoursScheduled Weekly Hours0

• Work ShiftWork Shift(empty)

• Recruiting Start DateRecruiting Start Date08/25/2026

• Target Hire DateTarget Hire Date08/25/2026

• Target End DateTarget End Date(empty)

Additional Information

• Union Membership from Job ProfileUnion Membership from Job Profile(empty)
• Allowed Unions from Job ProfileAllowed Unions from Job Profile(empty)

Collective Agreement Details

• Collective AgreementCollective Agreement(empty)

• Job DescriptionJob DescriptionKey Responsibilities

• Design, engineer, deploy, and support enterprise AI infrastructure and platform capabilities.

• Onboard and integrate enterprise AI platforms with enterprise identity, networking, security, monitoring, and operational services.

• Engineer AI developer environments, AI workspaces, API connectivity, model access, and platform integrations.

• Develop reusable platform components, reference implementations, and engineering patterns to accelerate enterprise AI adoption.

• Develop Infrastructure as Code (IaC) solutions using Terraform, CFT, Bicep, ARM, Ansible, or equivalent technologies.

• Build and maintain CI/CD pipelines for provisioning, configuration, deployment, and lifecycle management of AI platforms.

• Automate infrastructure provisioning, platform operations, configuration management, and operational workflows using scripting and DevOps practices.

• Implement platform monitoring, logging, observability, backup, disaster recovery, high availability, and performance optimization solutions.

• Troubleshoot complex infrastructure, networking, platform, and integration issues across enterprise AI environments.

• Support operational excellence through proactive monitoring, incident resolution, and continuous service improvement.

• Essential Requirements

• Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.

• 5+ years of experience in AI Infrastructure Engineering, Cloud Engineering and DevOps toolsets

• Relevant Cloud, Kubernetes, DevOps, Security, or AI certifications.

• Experience engineering enterprise AI platforms supporting Generative AI and AI-enabled workloads.

• Understanding of LLMs, AI APIs, AI agents, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), vector databases, model access patterns, and enterprise AI platform architecture.

• Enterprise AI ecosystems such as ChatGPT Enterprise, Claude, Gemini, Azure AI Foundry, AWS Bedrock, AgentCore, Vertex AI, Strands Agents SDK, LangGraph, CrewAI, Run.AI or SLURM or open-source AI platforms.

• Kubernetes & Container Platforms

• Infrastructure as Code (IaC), DevSecOps & CI/CD

• Desirable Requirements:

• AWS & Azure Monitor, Prometheus, Grafana, Log Analytics, Kusto Query Language (KQL), or equivalent monitoring platforms

• AI Developer Platforms (JupyterLab, VS Code, AI Workstations, Claude Cowork).onsibilities

Preferred candidate profile