Associate Distinguished Engineer (Agentic AI Architect)

Job description

**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 (18500+ experts across 40 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** - Experience : 13+ years - Relevant experience in AI/ML, Data Science, Intelligent Automation, or Generative AI, including architecting and delivering enterprise-scale AI solutions. - Strong expertise in Agentic AI, multi-agent systems, and enterprise AI application architecture. - Proven experience designing autonomous AI workflows, agent orchestration, hierarchical agent systems, and human-in-the-loop architectures. - Deep understanding of AI application solution design, enterprise architecture principles, and scalable distributed systems. - Extensive experience with LLM application frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, LlamaIndex, OpenAI Agent SDK, Google ADK, and Model Context Protocol (MCP). - Strong expertise in Prompt Engineering, Retrieval-Augmented Generation (RAG), GraphRAG, Agentic RAG, semantic search, embeddings, vector databases, and knowledge graphs. - Experience designing enterprise knowledge systems, memory architectures, context management, and retrieval frameworks. - Strong programming skills in Python with proficiency in at least one additional language such as Java, JavaScript/TypeScript, C#, or Go. - Experience developing production-grade AI-enabled applications using modern software engineering practices. - Strong knowledge of APIs, microservices, distributed systems, cloud-native application development, and event-driven architectures. - Experience with cloud platforms including Azure, AWS, or Google Cloud Platform. - Hands-on experience with Kubernetes, containerization, CI/CD pipelines, DevSecOps, MLOps, LLMOps, and AgentOps. - Experience implementing AI governance, guardrails, observability, monitoring, evaluation frameworks, and responsible AI practices. - Familiarity with AI-assisted software development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, OpenAI Codex, and AI-powered SDLC platforms. - Strong consulting, stakeholder management, and executive communication skills. - Proven experience leading enterprise AI transformation initiatives, technical workshops, solution assessments, and architecture reviews. - Experience preparing technical proposals, RFP responses, solution estimations, and executive presentations. - Knowledge of Knowledge Graphs, ontology design, semantic data models, AI evaluation frameworks, and synthetic data generation is an added advantage. - Industry experience across Retail, Manufacturing, Telecom, Financial Services, Healthcare, CPG, or similar enterprise domains is preferred. **Responsibilities** - Architect and design enterprise-scale Agentic AI and Generative AI solutions aligned with business objectives and technology strategies. - Define scalable architectures for multi-agent collaboration, autonomous workflows, hierarchical agent systems, planners, orchestrators, supervisors, and human-in-the-loop processes. - Design and implement advanced reasoning frameworks including ReAct, Plan-and-Execute, Reflection, Tree-of-Thoughts, and other agentic AI patterns. - Develop enterprise AI architectures incorporating RAG, GraphRAG, Knowledge Graphs, Semantic Search, Enterprise Search, and intelligent knowledge systems. - Define strategies for agent communication, memory management, context handling, tool integration, and lifecycle management. - Architect scalable AI platforms supporting enterprise-wide agentic workloads with robust governance, security, and observability. - Establish standards and best practices for AI Engineering, AgentOps, LLMOps, MLOps, AI governance, evaluation, monitoring, and compliance. - Design reusable AI accelerators, reference architectures, enterprise frameworks, and AI platform capabilities. - Evaluate commercial and open-source LLMs, optimize model selection, orchestration strategies, and inference performance. - Integrate AI solutions with enterprise applications, APIs, microservices, event-driven systems, and cloud-native platforms. - Drive AI-assisted software development practices across the SDLC, including requirements analysis, coding, testing, documentation, deployment, and maintenance. - Lead AI discovery workshops, architecture assessments, proof-of-concepts, MVPs, and enterprise transformation initiatives. - Provide strategic consulting to business and technology leaders on AI adoption, architecture, governance, and innovation. - Mentor architects, engineers, data scientists, and technical teams by establishing architecture standards and AI engineering best practices. - Support presales activities including solutioning, proposals, RFP responses, effort estimation, demonstrations, and executive presentations. - Collaborate with cross-functional teams to deliver innovative, secure, scalable, and production-ready AI-enabled enterprise solutions. - Drive continuous innovation by evaluating emerging AI technologies, frameworks, and industry trends to enhance organizational AI capabilities and competitive advantage. **Qualifications** Bachelor’s or master’s degree in computer science, Information Technology, or a related field.