Associate Distinguished Engineer (Solution Architect -GenAI,RAG + AI)

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!

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.