Associate Distinguished Engineer (Agentic AI Architect)
On-siteIndia, Tennessee, United States
Job Summary
Design and architect enterprise-scale Agentic AI and Generative AI solutions aligned with business objectives, defining scalable architectures for multi-agent collaboration and intelligent orchestration. Lead the design of advanced reasoning frameworks, agent communication protocols, and tool integration strategies while establishing governance frameworks, guardrails, and observability standards. Architect enterprise knowledge systems leveraging RAG, GraphRAG, and Semantic Search to integrate structured and unstructured data sources. Evaluate LLM selection and inference strategies across commercial and open-source platforms, then architect scalable AI platforms supporting enterprise-wide workloads and reusable accelerators. Establish engineering standards for LLMOps, AgentOps, and MLOps, defining integration patterns using APIs and microservices. Drive adoption of AI-enabled software development practices across the SDLC and act as a trusted advisor to stakeholders on AI strategy and transformation initiatives. Lead Proof of Concepts and MVPs from concept through production deployment while mentoring architects and engineers.
Required Qualifications
- 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
- Bachelor's or master's degree in computer science, Information Technology, or a related field
Desired Qualifications
- 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
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