RESUME AND JOB
Nagarro
Location: India, India | Job ID: REF48952G
**Why Join Nagarro?**
Nagarro stands out in Nagarro Careers with its unwavering Caring Mindset, prioritizing employee well-being through personalized development paths, mental health support, and work-life harmony. As a Fluidic Enterprise, we offer seamless global mobility, allowing you to collaborate on diverse projects across India and international hubs. Embrace Global Opportunities with exposure to Fortune 500 clients, accelerating your career in Software Engineering Jobs focused on AI and digital transformation. Enjoy competitive salaries, performance bonuses, and comprehensive benefits that reflect our commitment to your success.
**Digital Engineering Excellence**
Dive into Digital Engineering Excellence at Nagarro, leading AI Architecture Design for scalable ecosystems including RAG, data pipelines, MCP, and agentic AI. Leverage expertise in LLM frameworks like Lang Graph, Crew AI, and Semantic Kernel, alongside RAG tools such as Lang Chain and Llama Index. Master MLOps on Azure, GCP, AWS with Kubernetes, Docker, and MLflow. Own data infrastructure with vector databases like Pinecone and Weaviate, ensuring context-aware systems and governance. Our Principal Engineers build reusable accelerators, optimize retrieval frameworks, and deliver MVPs in 90-day cycles, embodying end-to-end ownership and system thinking.
**Your Impact at Nagarro**
As a Principal Engineer, your impact will redefine enterprise AI. Mentor full-stack teams, track ROI through automation and cost savings, and integrate emerging tools like Open Devin and Model Context API. Lead from concept to production, fostering a culture of continuous improvement and measurable delivery. In Nagarro Careers, you'll thrive in Software Engineering Jobs that demand data-awareness and innovation, contributing to responsible AI deployments with Prometheus, Grafana, and Open Telemetry. Join a community where your leadership drives business value, global projects, and lasting legacy in AI excellence. (452 words)
REQUIREMENT: Total years of experience 13 to 15 years. AI Architecture Design Architect scalable AI ecosystems covering RAG, data pipelines, MCP, and agentic AI. Data & Knowledge Infrastructure Ownership Define how data flows into embeddings, vector stores, and retrieval layers for context-aware systems. MLOps & Cloud Governance Set up CI/CD, monitoring, and cost-optimization for AI workloads across Azure/GCP/AWS. Modal Context Protocol (MCP) Integration Build interoperability between AI systems, enterprise data, and delivery tools. RAG Strategy & Data Governance Define RAG templates, data governance standards, and retrieval optimization frameworks. Concept-to-MVP Leadership Deliver AI MVPs in 90-day cycles with measurable ROI and governance alignment. Accelerator Ownership Build reusable RAG pipelines, prompt templates, and orchestration accelerators. Team & Capability Development Mentor full-stack AI developers; set architecture, data, and delivery standards. Business Value Measurement Track ROI, automation %, and cost savings per AI deployment LLM & Agent Frameworks: Lang Graph, Crew AI, Auto Gen, Semantic Kernel RAG & Data Pipelines: Lang Chain RAG, Llama Index, Databricks, Airflow, Pandas Vector Databases: Pinecone, Chroma, FAISS, Weaviate Cloud & MLOps: MLflow, Kubernetes, Docker, Azure ML, Vertex AI MCP & Interoperability: Modal Context Protocol, Context Graphs Governance & Monitoring: Prometheus, Grafana, Open Telemetry, Responsible AI Toolkit Emerging Tools: Open Devin, Model Context API, Hugging GPT. Core Traits: End-to-end ownership, data-awareness, system thinking, and measurable delivery accountability. RESPONSIBILITIES: Writing and reviewing great quality code Understanding functional requirements thoroughly and analysing the client’s needs in the context of the project Envisioning the overall solution for defined functional and non-functional requirements, and being able to define technologies, patterns and frameworks to realize it Determining and implementing design methodologies and tool sets Enabling application development by coordinating requirements, schedules, and activities. Being able to lead/support UAT and production roll outs Creating, understanding and validating WBS and estimated effort for given module/task, and being able to justify it Addressing issues promptly, responding positively to setbacks and challenges with a mindset of continuous improvement Giving constructive feedback to the team members and setting clear expectations. Helping the team in troubleshooting and resolving of complex bugs Coming up with solutions to any issue that is raised during code/design review and being able to justify the decision taken Carrying out POCs to make sure that suggested design/technologies meet the requirements
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
AI Architecture Design (RAG, data pipelines, MCP, agentic AI), MLOps & Cloud Governance (Azure, GCP, AWS, MLflow, Kubernetes), LLM & Agent Frameworks (Lang Graph, Crew AI, Auto Gen, Semantic Kernel), RAG & Data Pipelines (Lang Chain, Llama Index, Databricks, Airflow), Vector Databases (Pinecone, Chroma, FAISS, Weaviate), Team Mentorship & Leadership, End-to-end Ownership & System Thinking
Search keywords: Nagarro Careers, India Engineering Jobs, Digital Transformation Roles, AI Architecture Design (RAG, data pipelines, MCP, agentic AI), MLOps & Cloud Governance (Azure, GCP, AWS, MLflow, Kubernetes), LLM & Agent Frameworks (Lang Graph, Crew AI, Auto Gen, Semantic Kernel) Opportunities.
Salary details available upon request
4,500,000 - 7,560,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
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Nagarro
Location: India, India | Job ID: REF48952G
**Why Join Nagarro?**
Nagarro stands out in Nagarro Careers with its unwavering Caring Mindset, prioritizing employee well-being through personalized development paths, mental health support, and work-life harmony. As a Fluidic Enterprise, we offer seamless global mobility, allowing you to collaborate on diverse projects across India and international hubs. Embrace Global Opportunities with exposure to Fortune 500 clients, accelerating your career in Software Engineering Jobs focused on AI and digital transformation. Enjoy competitive salaries, performance bonuses, and comprehensive benefits that reflect our commitment to your success.
**Digital Engineering Excellence**
Dive into Digital Engineering Excellence at Nagarro, leading AI Architecture Design for scalable ecosystems including RAG, data pipelines, MCP, and agentic AI. Leverage expertise in LLM frameworks like Lang Graph, Crew AI, and Semantic Kernel, alongside RAG tools such as Lang Chain and Llama Index. Master MLOps on Azure, GCP, AWS with Kubernetes, Docker, and MLflow. Own data infrastructure with vector databases like Pinecone and Weaviate, ensuring context-aware systems and governance. Our Principal Engineers build reusable accelerators, optimize retrieval frameworks, and deliver MVPs in 90-day cycles, embodying end-to-end ownership and system thinking.
**Your Impact at Nagarro**
As a Principal Engineer, your impact will redefine enterprise AI. Mentor full-stack teams, track ROI through automation and cost savings, and integrate emerging tools like Open Devin and Model Context API. Lead from concept to production, fostering a culture of continuous improvement and measurable delivery. In Nagarro Careers, you'll thrive in Software Engineering Jobs that demand data-awareness and innovation, contributing to responsible AI deployments with Prometheus, Grafana, and Open Telemetry. Join a community where your leadership drives business value, global projects, and lasting legacy in AI excellence. (452 words)
REQUIREMENT: Total years of experience 13 to 15 years. AI Architecture Design Architect scalable AI ecosystems covering RAG, data pipelines, MCP, and agentic AI. Data & Knowledge Infrastructure Ownership Define how data flows into embeddings, vector stores, and retrieval layers for context-aware systems. MLOps & Cloud Governance Set up CI/CD, monitoring, and cost-optimization for AI workloads across Azure/GCP/AWS. Modal Context Protocol (MCP) Integration Build interoperability between AI systems, enterprise data, and delivery tools. RAG Strategy & Data Governance Define RAG templates, data governance standards, and retrieval optimization frameworks. Concept-to-MVP Leadership Deliver AI MVPs in 90-day cycles with measurable ROI and governance alignment. Accelerator Ownership Build reusable RAG pipelines, prompt templates, and orchestration accelerators. Team & Capability Development Mentor full-stack AI developers; set architecture, data, and delivery standards. Business Value Measurement Track ROI, automation %, and cost savings per AI deployment LLM & Agent Frameworks: Lang Graph, Crew AI, Auto Gen, Semantic Kernel RAG & Data Pipelines: Lang Chain RAG, Llama Index, Databricks, Airflow, Pandas Vector Databases: Pinecone, Chroma, FAISS, Weaviate Cloud & MLOps: MLflow, Kubernetes, Docker, Azure ML, Vertex AI MCP & Interoperability: Modal Context Protocol, Context Graphs Governance & Monitoring: Prometheus, Grafana, Open Telemetry, Responsible AI Toolkit Emerging Tools: Open Devin, Model Context API, Hugging GPT. Core Traits: End-to-end ownership, data-awareness, system thinking, and measurable delivery accountability. RESPONSIBILITIES: Writing and reviewing great quality code Understanding functional requirements thoroughly and analysing the client’s needs in the context of the project Envisioning the overall solution for defined functional and non-functional requirements, and being able to define technologies, patterns and frameworks to realize it Determining and implementing design methodologies and tool sets Enabling application development by coordinating requirements, schedules, and activities. Being able to lead/support UAT and production roll outs Creating, understanding and validating WBS and estimated effort for given module/task, and being able to justify it Addressing issues promptly, responding positively to setbacks and challenges with a mindset of continuous improvement Giving constructive feedback to the team members and setting clear expectations. Helping the team in troubleshooting and resolving of complex bugs Coming up with solutions to any issue that is raised during code/design review and being able to justify the decision taken Carrying out POCs to make sure that suggested design/technologies meet the requirements
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
AI Architecture Design (RAG, data pipelines, MCP, agentic AI), MLOps & Cloud Governance (Azure, GCP, AWS, MLflow, Kubernetes), LLM & Agent Frameworks (Lang Graph, Crew AI, Auto Gen, Semantic Kernel), RAG & Data Pipelines (Lang Chain, Llama Index, Databricks, Airflow), Vector Databases (Pinecone, Chroma, FAISS, Weaviate), Team Mentorship & Leadership, End-to-end Ownership & System Thinking
Search keywords: Nagarro Careers, India Engineering Jobs, Digital Transformation Roles, AI Architecture Design (RAG, data pipelines, MCP, agentic AI), MLOps & Cloud Governance (Azure, GCP, AWS, MLflow, Kubernetes), LLM & Agent Frameworks (Lang Graph, Crew AI, Auto Gen, Semantic Kernel) Opportunities.
Salary details available upon request
4,500,000 - 7,560,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Get personalized recommendations to optimize your resume specifically for Principal Engineer - Careers at Nagarro. Takes only 15 seconds!
Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.
Answer 10 quick questions to check your fit for Principal Engineer - Careers at Nagarro @ Nagarro.

No related jobs found at the moment.

© 2026 Pointers. All rights reserved.