Associate Distinguished Engineer (Agentic AI Architect)

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

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.

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