Principal Engineer, Agentic AI

Nagarro · Gurugram, , India

  • Senior
  • Full-time
  • Posted 2026-09-21
  • Confirmed live on 25 September 2026

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Job description

Job Description
REQUIREMENTS:

• Total experience 11+ years.

• Should have experience in software engineering, with strong depth in Python.

• Strong expertise in Machine Learning, Deep Learning, and statistical modeling

• Experience designing scalable ML systems and production pipelines

• Hands-on experience with agentic frameworks (LangGraph, CrewAI, AutoGen) and multi-agent orchestration

• 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.

• Design end-to-end AI/ML architectures, including scalable, secure, and production-ready systems using Machine Learning, Deep Learning, and Large Language Models (LLMs). Establish best practices for building robust and reusable AI platforms.

• Design scalable, secure, and cost-efficient backend platforms for LLM inference, RAG pipelines, and agent-based orchestration.

• 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.

Qualifications
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

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 (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!

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