Associate Director Technology

Job 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! **Roles and Responsibilities:** - Experience: 13+ years - Strong experience in AI/ML, Data Science, Intelligent Automation, or Generative AI, including enterprise-scale solution architecture. - Strong expertise in artificial intelligence architectures such as Agentic AI and machine learning algorithms like LangGraph. - Proficiency in programming language Python . - Strong expertise in designing and implementing Agentic AI solutions and AI application architectures. - Strong experience in Design, prototype, and scale production-grade AI applications focusing on AI Agents, Knowledge Graphs, and Databricks AI (Genie, MLOps)to solve complex enterprise use cases like NLP-to-SQL and unstructured document Q&A. - Should have hands-on experience building agentic workflows (e.g., LangGraph, AutoGen, CrewAI) and agent loops. - Should have experience with Knowledge Graphs (e.g., Neo4j) and implementing GraphRAG / Hybrid Retrieval. - Should have experience with Databricks Genie Agents, Genie Ontology, MLflow, and Databricks Vector Search / Unity Catalog - Should be able to build text-to-SQL agents with schema mapping and query execution safety. - Layout-aware parsing, chunking, and Q&A retrieval over complex PDFs/documents. **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.