Associate Distinguished Engineer (Agentic AI Architect)

👋🏼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! Requirements Experience : 13+ years Strong experience in AI/ML, Data Science, Intelligent Automation, or Generative AI, including enterprise-scale solution architecture. Strong expertise in designing and implementing Agentic AI solutions and AI application architectures. Hands-on experience with multi-agent systems, autonomous workflows, and AI orchestration frameworks. Deep understanding of reasoning frameworks such as ReAct, Plan-and-Execute, Reflection, and Tree-of-Thoughts. Strong experience designing enterprise AI applications leveraging RAG, GraphRAG, Knowledge Graphs, Semantic Search, and Enterprise Search. Expertise in LLM-powered applications, prompt engineering, embeddings, semantic retrieval, model evaluation, and fine-tuning. Hands-on experience with AI application frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, LlamaIndex, OpenAI Agent SDK, Google ADK, and MCP (Model Context Protocol). Strong programming skills in Python, along with proficiency in Java, JavaScript/TypeScript, C#, Go, or similar programming languages. Experience building production-grade AI applications using APIs, microservices, distributed systems, and cloud-native architectures. Strong knowledge of vector databases, graph databases, enterprise data platforms, and AI engineering best practices. Experience implementing AI-assisted software development workflows, developer productivity tools, and AI-enabled application development. Expertise in cloud platforms such as AWS, Azure, or GCP, along with Kubernetes, containerization, CI/CD, DevSecOps, MLOps, LLMOps, and AgentOps. Strong understanding of AI governance, observability, monitoring, evaluation frameworks, and responsible AI practices. Excellent consulting, stakeholder management, communication, and presentation skills. Proven ability to lead cross-functional teams, mentor technical professionals, and drive enterprise AI transformation initiatives. Experience across industries such as Financial Services, Retail, Telecom, Manufacturing, Healthcare, or CPG is preferred. Experience with Knowledge Graphs, ontology design, semantic data models, AI evaluation frameworks, or open-source AI contributions is an added advantage. Cloud Architect and AI certifications are preferred. Responsibilities Design and architect enterprise-scale Agentic AI and Generative AI solutions aligned with business objectives. Define scalable architectures for multi-agent collaboration, autonomous workflows, human-in-the-loop systems, and intelligent orchestration. Lead the design and implementation of advanced reasoning frameworks, agent communication protocols, memory management, and tool integration strategies. Establish AI governance frameworks, guardrails, evaluation methodologies, observability standards, and production best practices. Architect enterprise knowledge systems leveraging RAG, GraphRAG, Knowledge Graphs, Semantic Search, and Enterprise Search technologies. Design retrieval architectures that integrate structured and unstructured enterprise data sources. Define memory architectures, context management strategies, and enterprise knowledge frameworks for AI applications. Evaluate and optimize LLM selection, orchestration, inference strategies, and model performance across commercial and open-source platforms. Architect scalable AI platforms supporting enterprise-wide AI workloads, reusable accelerators, and reference architectures. Establish engineering standards for AI Engineering, LLMOps, AgentOps, MLOps, deployment, monitoring, and lifecycle management. Define integration patterns using APIs, microservices, event-driven architectures, and workflow orchestration frameworks. Drive adoption of AI-enabled software development practices across the SDLC, including coding, testing, documentation, deployment, and maintenance. Act as a trusted advisor to business and technology stakeholders on AI strategy, architecture, and enterprise transformation initiatives. Conduct architecture assessments, discovery workshops, AI strategy engagements, and solution design sessions. Lead Proof of Concepts (PoCs), MVPs, and enterprise AI implementations from concept through production deployment. Mentor architects, engineers, and data scientists while promoting engineering excellence and architectural best practices. Support solution development activities including proposals, RFP responses, effort estimation, and executive presentations. Collaborate with cross-functional teams to deliver scalable, secure, and high-performance AI solutions that meet business and technology goals. Continuously evaluate emerging AI technologies, frameworks, and industry trends to drive innovation and enhance enterprise AI capabilities. Bachelor’s or master’s degree in computer science, Information Technology, or a related field.