Associate Distinguished Engineer (Agentic AI Architect)

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
• 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.

Qualifications

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

Additional Information

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