14 days ago
Remote, IndiaStaff+
Responsibilities
- Translate client business use cases and technical requirements into durable technical designs.
- 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 orchestration.
- Define frontend architecture and UX patterns for conversational interfaces, copilots, and intelligent dashboards.
- Lead complex GenAI workflows combining LLMs, tools, APIs, structured data, and user context.
- Build reusable GenAI platform components, SDKs, and frameworks for multiple teams or products.
- Establish engineering standards for prompt design, model integration, evaluation, observability, governance, and responsible AI.
- Partner with product, design, data, business, and technical leaders to define scalable solutions and technical strategy.
- Review critical designs and codebases, resolve complex technical issues, mentor engineers, and improve engineering standards.
- Lead technical discovery, solutioning, architecture reviews, proofs of concept, and client or executive-facing workshops.
- Define technology choices, architectural patterns, non-functional requirements, design documentation, and implementation guidelines.
Requirements
- 9+ years of total professional experience.
- Strong software engineering experience with substantial depth in Python.
- Experience developing microservices and APIs with Python, FastAPI, and Node.js to embed AI and deep learning models into enterprise applications.
- Proven experience architecting and delivering production-grade Generative AI applications at scale.
- Strong system design skills across backend, frontend, and AI infrastructure layers.
- Experience architecting and implementing ML, Generative AI, and Agentic AI solutions involving LLMs, RAG, and autonomous agents.
- Experience with enterprise architecture, solution design, distributed systems, and hybrid or cloud AI deployments.
- Experience building end-to-end AI pipelines and integrating vector databases such as Pinecone, Weaviate, and Milvus.
- Experience with cloud platforms including AWS, Azure, or GCP, as well as secure access control and production-grade deployment practices.
- Ability to define technical strategy, influence architecture across teams, mentor engineers, and communicate complex AI concepts to non-technical audiences.
- Knowledge of AI governance, responsible AI, multi-cloud AI platform architecture, AgentOps or GenAIOps, knowledge graphs, and semantic layer architecture.
- Bachelor’s or master’s degree in computer science, information technology, or a related field.
Categories
About Nagarro
Nagarro provides digital engineering and IT consulting services to enterprises, delivering custom software development, cloud modernization, data and analytics, IoT, and digital commerce solutions. Its business model centers on project-based and managed services across the full product lifecycle, from strategy and design to build and operations. Nagarro is a public company headquartered in Munich and listed on the Frankfurt Stock Exchange, with global delivery across multiple regions.