Specialist Associate Principal Engineer, AI Architect India, Gurugram Employee

Nagarro; Gurugram District; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Nagarro seeks an Associate Principal Engineer, AI Architect to lead architecture for AI-powered applications across Python, React, and GenAI at scale. You will design secure, scalable backend platforms for LLM inference, orchestrate RAG pipelines, and drive AI-native frontend patterns.

Role requires 9+ years’ experience, deep cloud/GCP knowledge (Vertex AI, BigQuery), MLOps, and strong stakeholder communication to influence senior leadership. Hybrid work model preferred.

Qualifications

• Total experience 9+ years.
• Strong depth in Python.
• Proven experience architecting and delivering production-grade Generative AI applications at scale.
• Deep understanding of LLM integration patterns, RAG systems, and AI-driven UX design.
• Strong system design skills across backend, frontend, and AI infrastructure layers.
• Experience defining technical strategy and influencing architecture across teams or pods.
• Experience with microservices, APIs, and scalable backend systems.
• MLOps practices including CI/CD, model versioning, monitoring, and governance.
• Hands-on experience with tools such as MLflow, Vertex AI, Kubeflow, or similar.
• Deep experience with cloud platforms, especially GCP (Vertex AI, BigQuery) and/or Databricks.
• Strong grasp of security, privacy, and governance considerations for enterprise AI.
• Ability to translate ambiguous business problems into durable technical architectures.
• Excellent communication skills, with the ability to influence senior stakeholders and technical leadership.

Responsibilities

• Understand the client’s business use cases and convert them into technical design meeting requirements.
• Own the architecture and technical vision for AI-powered applications built with Python, React, and GenAI.
• Design scalable, secure backend platforms for LLM inference, RAG pipelines, and agent-based orchestration.
• Define frontend architecture and UX patterns for AI-native applications, including conversational interfaces and dashboards.
• Lead GenAI workflows that combine LLMs, tools, APIs, data, and user context.
• Establish engineering standards for prompt design, model integration, evaluation and observability.
• Drive platformisation by building reusable components, SDKs, and frameworks.
• Collaborate with product, design, data, and business leaders to translate strategy into scalable solutions.
• Review designs and codebases, unblock teams on complex challenges, raise engineering bar.
• Lead technical discovery and solutioning for high-impact initiatives and workshops when required.
• Ensure enterprise readiness: security, privacy, governance, and responsible AI practices.
• Use AI-assisted development tools to accelerate delivery while preserving quality.
• Map decisions to requirements and translate to developers.
• Identify multiple solutions and select the best option for client needs.
• Define guidelines and benchmarks for NFR during projects.
• Write and review design documents detailing architecture and high-level design.
• Review architecture for extensibility, scalability, security, and UX; enforce best practices.
• Develop and design overall solution for functional and non-functional requirements; choose technologies and patterns.
• Relate technology integration scenarios to project needs and apply learnings.
• Resolve issues via root-cause analysis and justification of decisions.
• Carry out POCs to verify design/tech meets requirements.

Skills

Python

LLM integration

Generative AI

MLOps

Cloud platforms (GCP)

Vertex AI

Kubeflow

Microservices

APIs

Security & governance

Education

Bachelor’s or Master’s degree in Computer Science / Information Technology

Tools

MLflow

BigQuery

Databricks

Kubeflow

Job description

Associate Principal Engineer, AI Architect

• Full-time
• Service Region: South Asia

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 (18000+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in!

REQUIREMENTS:

• Total experience 9+ years.
• Should haveexperience in software engineering, with strong depth in Python.
• Should have proven experience architecting and delivering production-grade Generative AI applications at scale.
• Should have deep understanding of LLM integration patterns, RAG systems, and AI-driven UX design.
• Should have strong system design skills across backend, frontend, and AI infrastructure layers.
• Must have experience defining technical strategy and influencing architecture across teams or pods.
• Must have experience with microservices, APIs, and scalable backend systems.
• Strong experience in MLOps practices including CI/CD, model versioning, monitoring, and governance.
• Hands-on experience with tools such as MLflow, Vertex AI, Kubeflow, or similar.
• Should have deep experience with cloud platforms, especially GCP (Vertex AI, BigQuery) and/or Databricks
• Should have strong grasp of security, privacy, and governance considerations for enterprise AI.
• Must have ability to translate ambiguous business problems into durable technical architectures.
• Should have excellent communication skills, with the ability to influence senior stakeholders and technical leadership.

RESPONSIBILITIES:

• Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Own the architecture and technical vision for AI-powered, user-facing applications built with Python, React, and Generative AI.
• Design scalable, secure, and cost-efficient backend platforms for LLM inference, RAG pipelines, and agent-based orchestration.
• Define frontend architecture and UX patterns for AI-native applications, including conversational interfaces, copilots, and intelligent dashboards.
• Lead the design and implementation of complex GenAI workflows that combine LLMs, tools, APIs, structured data, and user context.
• Establish engineering standards and best practices for prompt design, model integration, evaluation, and observability.
• Drive GenAI platformisation—building reusable components, SDKs, and frameworks used across multiple teams or products.
• Partner with product, design, data, and business leaders to translate strategic objectives into scalable technical solutions.
• Review critical designs and codebases, unblock teams on complex technical challenges, and raise the overall engineering bar.
• Lead technical discovery and solutioning for high-impact initiatives, including client or executive-facing workshops when required.
• Ensure enterprise readiness: security, privacy, compliance, governance, and responsible AI practices.
• Use AI-assisted development tools (e.g., Copilot, Claude Code) to accelerate delivery while maintaining production-grade quality.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the client’s requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
• Understanding and relating technology integration scenarios and applying these learnings in projects
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, 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.