Nagarro
Website:
nagarro.com
Company:
https://www.linkedin.com/company/nagarro
Seniority: Not Applicable
Industries: IT Services and IT Consulting
Job details:
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!
Job Description
REQUIREMENTS:
- Total experience 11+ years.
- Should have 10+ years of experience in software engineering, with strong depth in Python and modern frontend frameworks (React).
- Should have proven experience architecting and delivering production-grade Generative AI applications at scale.
- Design solutions and implement ML, generative AI and agentic AI models and algorithms, utilizing state-of-the-art algorithms.
- Should be able to drive backend deployment, security reviews, and QA pipelines, coordinate integration of RAG APIs and vector DB pipelines
- Should be able to work on integrating cloud with AI algorithms and On premises AI algorithms.
- Optimize existing AI models for improved performance, scalability, and efficiency.
- Should be able to develop and maintain AI pipelines, including data pre-processing, feature extraction, model training, and evaluation.
- Should be able to drive the team to build AI products and solutions, working in an agile methodology Manage delivery across pods building scalable AI and API services
- Should have deep understanding of LLM integration patterns, RAG systems, and AI-driven UX design.
- Should have experience in Datarobot for architecting and building GenAI Solutions, RAG Agents and Deployment
- Must have experience defining technical strategy and influencing architecture across teams or pods.
- Should have hands-on experience with cloud platforms (AWS, Azure, or GCP) and distributed systems.
- 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 scalable, secure, and cost-efficient backend platforms for LLM inference, RAG pipelines, and agent-based orchestration.
- Promote use of code quality agents and modern CI/CD practices.
- Collaborate with the Product Manager/Architect to define deliverables and technical strategy.
- Drive the integration of AI/ML capabilities into products using market trending libraries.
- 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.
- Troubleshoot and resolve issues related to AI models and implementations. Create and maintain documentation for AI models and their applications.
- 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.
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