Senior Staff Engineer (Cloud) - Careers at Nagarro
Nagarro
Senior Staff Engineer (Cloud) - Careers at Nagarro
Job Description
Senior Staff Engineer (Cloud) - Careers at Nagarro
Location: India, India | Job ID: REF54502O
**Why Join Nagarro?**
Nagarro's Caring Mindset sets us apart in the competitive landscape of tech careers. We prioritize your growth with tailored development programs, mental health support, and a Fluidic Enterprise model that adapts to your ambitions. Enjoy global opportunities across India and beyond, working on transformative projects for Fortune 500 clients. Our culture fosters innovation, offering equity in decision-making and a collaborative space where your voice drives change. Embrace work-life harmony with flexible hours, remote options, and comprehensive benefits that value your contributions.
**Digital Engineering Excellence**
At Nagarro, we lead in digital engineering, powering AI/ML workloads with tools like Terraform, Helm, Argo, Ray, and vector databases. As a Senior Staff Engineer, harness Python, Bash, and Go to build resilient LLMOps pipelines, optimize inference for latency and cost, and ensure production-grade observability. Our platform teams thrive on CI/CD automation, security governance, and performance tuning for distributed systems. With exposure to fine-tuning OpenAI and Anthropic models, you'll pioneer cost-optimized AI strategies in a dynamic, cloud-native ecosystem.
**Your Impact at Nagarro**
Make a tangible difference by designing infrastructure for training, serving, and monitoring LLMs, collaborating with ML and product teams to operationalize AI solutions. Your expertise in model serving frameworks and accelerator stacks will drive efficiency, reliability, and scalability. In Nagarro Careers, you'll influence global AI deployments, mentor juniors, and shape the future of enterprise intelligence. Join our senior-level Software Engineering Jobs to unleash innovation with a Caring Mindset, and propel your career in a company that values bold ideas and lasting impact. (452 words)
Role 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
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Key Responsibilities
- Design and manage scalable infrastructure for LLMs (training, fine-tuning, serving, monitoring)
- Build and maintain LLMOps pipelines (deployment, versioning, rollback, monitoring, evaluation)
- Optimize inference performance (latency, throughput, cost) on GPU/accelerator stacks
- Implement CI/CD, IaC, and automation for AI/ML workloads
- Ensure observability, reliability, governance, security, compliance for LLM systems
- Collaborate with ML, platform, and product teams to operationalize AI solutions
What You Bring (Qualifications)
- 7.5+ years (10-12 preferred) in infrastructure, platform, DevOps, or MLOps
- Strong experience with cloud platforms and Kubernetes
- Hands-on with deploying/operating LLMs and GPU infrastructure
- Bachelor’s or Master’s in Computer Science, IT, or related field
Core Skills
Cloud platforms (AWS/GCP/Azure), Kubernetes, LLM deployment and operations (OpenAI, Anthropic, open-source), GPU infrastructure and model serving frameworks, Vector databases, Python programming, Terraform, Helm, Argo, Ray, LLMOps pipelines (fine-tuning, RAG, prompt management), Monitoring, logging, performance tuning, CI/CD and IaC
Why Nagarro? (Benefits)
- Caring Mindset: Personalized growth plans and well-being support
- Fluidic Enterprise: Flexible work environment and agile project opportunities
- Global opportunities: Work across international teams and locations
- Professional development: Continuous learning in cutting-edge AI and cloud tech
- Collaborative culture: Impactful roles with cross-functional innovation
Locations
- India, India
Salary
Salary details available upon request
3,500,000 - 6,480,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Cloud platforms (AWS/GCP/Azure)intermediate
- Kubernetesintermediate
- LLM deployment and operations (OpenAI, Anthropic, open-source)intermediate
- GPU infrastructure and model serving frameworksintermediate
- Vector databasesintermediate
- Python programmingintermediate
- Terraform, Helm, Argo, Rayintermediate
- LLMOps pipelines (fine-tuning, RAG, prompt management)intermediate
- Monitoring, logging, performance tuningintermediate
- CI/CD and IaCintermediate
Required Qualifications
- 7.5+ years (10-12 preferred) in infrastructure, platform, DevOps, or MLOps (experience)
- Strong experience with cloud platforms and Kubernetes (experience)
- Hands-on with deploying/operating LLMs and GPU infrastructure (experience)
- Bachelor’s or Master’s in Computer Science, IT, or related field (experience)
Responsibilities
- Design and manage scalable infrastructure for LLMs (training, fine-tuning, serving, monitoring)
- Build and maintain LLMOps pipelines (deployment, versioning, rollback, monitoring, evaluation)
- Optimize inference performance (latency, throughput, cost) on GPU/accelerator stacks
- Implement CI/CD, IaC, and automation for AI/ML workloads
- Ensure observability, reliability, governance, security, compliance for LLM systems
- Collaborate with ML, platform, and product teams to operationalize AI solutions
Benefits
- general: Caring Mindset: Personalized growth plans and well-being support
- general: Fluidic Enterprise: Flexible work environment and agile project opportunities
- general: Global opportunities: Work across international teams and locations
- general: Professional development: Continuous learning in cutting-edge AI and cloud tech
- general: Collaborative culture: Impactful roles with cross-functional innovation
Tags & Categories
Answer 10 quick questions to check your fit for Senior Staff Engineer (Cloud) - Careers at Nagarro @ Nagarro.
Related Books and Jobs
Senior Staff Engineer (Cloud) - Careers at Nagarro
Nagarro
Senior Staff Engineer (Cloud) - Careers at Nagarro
Job Description
Senior Staff Engineer (Cloud) - Careers at Nagarro
Location: India, India | Job ID: REF54502O
**Why Join Nagarro?**
Nagarro's Caring Mindset sets us apart in the competitive landscape of tech careers. We prioritize your growth with tailored development programs, mental health support, and a Fluidic Enterprise model that adapts to your ambitions. Enjoy global opportunities across India and beyond, working on transformative projects for Fortune 500 clients. Our culture fosters innovation, offering equity in decision-making and a collaborative space where your voice drives change. Embrace work-life harmony with flexible hours, remote options, and comprehensive benefits that value your contributions.
**Digital Engineering Excellence**
At Nagarro, we lead in digital engineering, powering AI/ML workloads with tools like Terraform, Helm, Argo, Ray, and vector databases. As a Senior Staff Engineer, harness Python, Bash, and Go to build resilient LLMOps pipelines, optimize inference for latency and cost, and ensure production-grade observability. Our platform teams thrive on CI/CD automation, security governance, and performance tuning for distributed systems. With exposure to fine-tuning OpenAI and Anthropic models, you'll pioneer cost-optimized AI strategies in a dynamic, cloud-native ecosystem.
**Your Impact at Nagarro**
Make a tangible difference by designing infrastructure for training, serving, and monitoring LLMs, collaborating with ML and product teams to operationalize AI solutions. Your expertise in model serving frameworks and accelerator stacks will drive efficiency, reliability, and scalability. In Nagarro Careers, you'll influence global AI deployments, mentor juniors, and shape the future of enterprise intelligence. Join our senior-level Software Engineering Jobs to unleash innovation with a Caring Mindset, and propel your career in a company that values bold ideas and lasting impact. (452 words)
Role 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
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Key Responsibilities
- Design and manage scalable infrastructure for LLMs (training, fine-tuning, serving, monitoring)
- Build and maintain LLMOps pipelines (deployment, versioning, rollback, monitoring, evaluation)
- Optimize inference performance (latency, throughput, cost) on GPU/accelerator stacks
- Implement CI/CD, IaC, and automation for AI/ML workloads
- Ensure observability, reliability, governance, security, compliance for LLM systems
- Collaborate with ML, platform, and product teams to operationalize AI solutions
What You Bring (Qualifications)
- 7.5+ years (10-12 preferred) in infrastructure, platform, DevOps, or MLOps
- Strong experience with cloud platforms and Kubernetes
- Hands-on with deploying/operating LLMs and GPU infrastructure
- Bachelor’s or Master’s in Computer Science, IT, or related field
Core Skills
Cloud platforms (AWS/GCP/Azure), Kubernetes, LLM deployment and operations (OpenAI, Anthropic, open-source), GPU infrastructure and model serving frameworks, Vector databases, Python programming, Terraform, Helm, Argo, Ray, LLMOps pipelines (fine-tuning, RAG, prompt management), Monitoring, logging, performance tuning, CI/CD and IaC
Why Nagarro? (Benefits)
- Caring Mindset: Personalized growth plans and well-being support
- Fluidic Enterprise: Flexible work environment and agile project opportunities
- Global opportunities: Work across international teams and locations
- Professional development: Continuous learning in cutting-edge AI and cloud tech
- Collaborative culture: Impactful roles with cross-functional innovation
Locations
- India, India
Salary
Salary details available upon request
3,500,000 - 6,480,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Cloud platforms (AWS/GCP/Azure)intermediate
- Kubernetesintermediate
- LLM deployment and operations (OpenAI, Anthropic, open-source)intermediate
- GPU infrastructure and model serving frameworksintermediate
- Vector databasesintermediate
- Python programmingintermediate
- Terraform, Helm, Argo, Rayintermediate
- LLMOps pipelines (fine-tuning, RAG, prompt management)intermediate
- Monitoring, logging, performance tuningintermediate
- CI/CD and IaCintermediate
Required Qualifications
- 7.5+ years (10-12 preferred) in infrastructure, platform, DevOps, or MLOps (experience)
- Strong experience with cloud platforms and Kubernetes (experience)
- Hands-on with deploying/operating LLMs and GPU infrastructure (experience)
- Bachelor’s or Master’s in Computer Science, IT, or related field (experience)
Responsibilities
- Design and manage scalable infrastructure for LLMs (training, fine-tuning, serving, monitoring)
- Build and maintain LLMOps pipelines (deployment, versioning, rollback, monitoring, evaluation)
- Optimize inference performance (latency, throughput, cost) on GPU/accelerator stacks
- Implement CI/CD, IaC, and automation for AI/ML workloads
- Ensure observability, reliability, governance, security, compliance for LLM systems
- Collaborate with ML, platform, and product teams to operationalize AI solutions
Benefits
- general: Caring Mindset: Personalized growth plans and well-being support
- general: Fluidic Enterprise: Flexible work environment and agile project opportunities
- general: Global opportunities: Work across international teams and locations
- general: Professional development: Continuous learning in cutting-edge AI and cloud tech
- general: Collaborative culture: Impactful roles with cross-functional innovation
Tags & Categories
Answer 10 quick questions to check your fit for Senior Staff Engineer (Cloud) - Careers at Nagarro @ Nagarro.
Related Books and Jobs