Principal Engineer at Nagarro

, , India -

Full Time

Start Date

Immediate

Expiry Date

28 Apr, 26

Salary

0.0

Posted On

28 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Architecture Design, Data Infrastructure Ownership, MLOps, Cloud Governance, RAG Strategy, Data Governance, Concept-to-MVP Leadership, Accelerator Ownership, Team Development, Business Value Measurement, LLM Frameworks, RAG Pipelines, Vector Databases, Cloud Tools, Governance Monitoring, Emerging Tools

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 39 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 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 Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field. Service Region: South Asia

Responsibilities

The Principal Engineer will be responsible for writing and reviewing high-quality code, understanding functional requirements, and envisioning overall solutions for projects. They will also lead UAT and production rollouts, address issues promptly, and provide constructive feedback to team members.