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AI infrastructure System Engineer Bangalore

Join Together AI as an AI Infrastructure Engineer (SRE) to ensure the reliability and scalability of user-facing services.

Location
Bangalore, India
Compensation
Not disclosed
Level
senior
Type
full time · Hybrid

Posted by employer 2 months ago

First seen on Joblaze 2 months ago

Last verified on the company career page 10 hours ago

Skills & Technologies

Requirements

Experience
7+ years
Education
Bachelor's degree

Not disclosed in this posting: compensation, visa sponsorship.

Joblaze summary

In the role of AI Infrastructure Engineer (SRE) at Together AI, the individual is tasked with ensuring the reliability and performance of user-facing services and production systems. Key responsibilities include managing infrastructure using tools like Ansible, Terraform, and Kubernetes, while also addressing incidents and optimizing system architecture. This position is ideal for seasoned professionals with over seven years of experience in SRE or related fields, particularly those with expertise in GPU-enabled Kubernetes clusters. Together AI fosters a collaborative environment, emphasizing innovation in AI infrastructure.

Joblaze insights

Quick facts

Is the AI infrastructure System Engineer Bangalore role remote?
It's hybrid — Together AI expects some on-site time in Bangalore, India.
How much experience is required?
At least 7 years of relevant experience for this AI infrastructure System Engineer Bangalore role.
Where is the role based?
Together AI is hiring for this position in Bangalore, India.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, Ansible, Kubernetes, Terraform.
What seniority level is this role?
Together AI targets senior candidates for this position.
Is this full-time or contract?
Full-time for this AI infrastructure System Engineer Bangalore role at Together AI.

From the original posting

About the Role

At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale.

If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk.

Responsibilities

  • Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention.
  • Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation.
  • Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers.
  • Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators.
  • Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads.
  • Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations.
  • Continuously improve deployment velocity, reliability, and operational efficiency through automation.
  • Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure.

Requirements

  • 3+ years building distributed systems, infrastructure platforms, or large-scale backend software.
  • Strong software engineering skills in Python, Go, or Rust.
  • Experience building platforms, automation systems, or developer infrastructure.
  • Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies.
  • Strong systems thinking with the ability to understand problems across hardware and software.
  • A passion for solving complex infrastructure challenges through software.
  • An automation-first mindset—if a task is repeated, your instinct is to build a system to eliminate it.

Bonus Experience

  • GPU infrastructure, CUDA, NCCL, NVLink/NVSwitch
  • InfiniBand or RoCE networking
  • Bare-metal provisioning and lifecycle management
  • Large-scale AI training or inference clusters
  • Hardware health monitoring and predictive failure detection
  • Distributed storage systems
  • AI agents and autonomous infrastructure operations

About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

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