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Senior Staff Engineer (Cloud) at Nagarro
, , India -
Full Time

Start Date

Immediate

Expiry Date

15 Apr, 26

Salary

0.0

Posted On

16 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Cloud Platforms, Kubernetes, LLMs, GPU Infrastructure, Model Serving Frameworks, Vector Databases, Python, Bash, Go, Monitoring, Logging, Performance Tuning, Terraform, Helm, Argo, Ray

Industry

IT Services and IT Consulting

Description
Company Description 👋🏼We're Nagarro We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500 experts across 36 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! Job Description REQUIREMENTS: Experience : 7.5+ Years 10-12 years in infrastructure, platform, DevOps, or MLOps roles Strong experience with cloud platforms (AWS/GCP/Azure) and Kubernetes Hands-on experience deploying and operating LLMs (OpenAI, Anthropic, open-source models) Proficiency with GPU infrastructure, model serving frameworks, and vector databases Strong programming skills in Python; experience with Bash/Go is a plus Experience with monitoring, logging, and performance tuning for distributed systems Preferred Qualifications Experience with LLM fine-tuning, RAG pipelines, and prompt/version management Familiarity with tools like Terraform, Helm, Argo, Ray, or similar Exposure to cost optimization strategies for large-scale AI systems Responsibilities: Design and manage scalable infrastructure for training, fine-tuning, serving, and monitoring LLMs Build and maintain LLMOps pipelines (deployment, versioning, rollback, monitoring, evaluation) Optimize inference performance (latency, throughput, cost) across GPU/accelerator stacks Implement CI/CD, IaC, and automation for AI/ML workloads Ensure observability, reliability, and governance of LLM systems in production Collaborate with ML, platform, and product teams to operationalize AI solutions Manage security, compliance, and access control for model and data pipelines Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field. Service Region: South Asia
Responsibilities
Design and manage scalable infrastructure for training, fine-tuning, serving, and monitoring LLMs. Collaborate with ML, platform, and product teams to operationalize AI solutions.