Associate Distinguished Engineer (Solution Architect - GenAI + RAG + Agentic AI, Cloud, data architecture, Integration Architecture)

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 a scale — across all devices and digital mediums, and our people exist everywhere in the world (18000+ experts across 36 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 Requirements 8+ years of experience in Solution Architecture, Technical Consulting, Pre-Sales Engineering, or related technology leadership roles. Minimum 2+ years of hands-on experience delivering AI/ML or Generative AI solutions. Strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, Prompt Engineering, and AI solution design. Experience designing enterprise-scale AI, data, cloud, and integration architectures. Hands-on experience with Azure AI Services, Azure OpenAI, AWS AI/ML, GCP AI, or equivalent cloud AI ecosystems. Strong understanding of MLOps, data pipelines, API integrations, and modern AI application architectures. Proven experience supporting RFPs, proposals, technical evaluations, solution estimations, and client presentations. Demonstrated ability to build and present executive-level demos, prototypes, and proof-of-concept solutions. Excellent communication, presentation, stakeholder management, and technical storytelling skills. Experience interacting with senior leadership, executive stakeholders, and business decision-makers. Strong analytical and problem-solving skills with the ability to evaluate technical and commercial trade-offs. Ability to create technical content, thought leadership materials, and industry-focused solution narratives. Experience working in cross-functional and matrixed environments involving sales, consulting, architecture, and delivery teams. Exposure to Public Sector, Government, Education, Higher Education, or Non-Profit domains is preferred. Familiarity with Microsoft, ServiceNow, and related enterprise technology ecosystems is highly desirable. Demonstrated thought leadership through publications, conference speaking engagements, webinars, or industry contributions is a plus. Responsibilities Act as the technical lead for AI solutioning, partnering with pre-sales, solution consultants, and planning teams across the deal lifecycle. Design scalable AI/ML and GenAI solution architectures for proposals, RFPs, client questionnaires, and competitive bids. Translate business challenges into technically sound, commercially viable, and value-driven AI solutions. Lead technical discovery workshops, solution walkthroughs, whiteboarding sessions, and stakeholder discussions. Build and deliver compelling demos, prototypes, and proof-of-concept solutions to support client engagements and proposal pursuits. Support effort estimation, solution sizing, technical feasibility assessments, and risk analysis during sales cycles. Serve as the subject matter expert for AI/ML, GenAI, data architecture, and emerging AI technologies. Develop thought leadership content including whitepapers, blogs, technical articles, and industry point-of-view documents. Represent the organization in webinars, conferences, industry forums, and executive client briefings. Track emerging trends across AI, Generative AI, cloud ecosystems, and intelligent automation platforms and translate them into actionable recommendations. Mentor solution consultants and pre-sales teams on AI solution positioning, architecture best practices, and technical storytelling. Create reusable AI accelerators, reference architectures, frameworks, and demo assets to improve proposal quality and reduce solutioning effort. Define and maintain a roadmap for AI accelerators and innovation assets aligned with business priorities and market demand. Ensure all reusable assets are documented, scalable, maintainable, and available for broader organizational adoption. Collaborate with architecture, design, engineering, and business teams to convert successful concepts into enterprise-grade reusable solutions. Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field.