• Design and own cloud-native architectures (AWS/Azure) for agentic AI workloads using Kubernetes/EKS, Terraform, Docker, serverless APIs, AWS Batch, and async orchestration frameworks (Celery, Step Functions, EventBridge, StoneBranch). • Define agentic system patterns using LangChain, LangGraph, Autogen, LlamaIndex, Pinecone, and other multi-agent frameworks; ensure consistency of prompt/tool design, memory/state handling, and workflow orchestration. • Architect vector database, RAG, embeddings pipelines, and model-serving endpoints (LLM/SLM) with strong emphasis on scalability and latency management. • Establish platform-wide standards for API gateway patterns, identity and auth (OAuth2, Cognito, Vault), secrets management, event contracts/schemas, and data governance. • Ensure holistic observability across multi-agent systems: tracing, metrics, logging, SLO/SLA definitions, synthetic checks, and incident response playbooks. • Lead architecture reviews, threat modeling, and performance benchmarking for agentic workloads. • Guide engineering teams through architectural decisions, distributed design principles, and production-readiness standards. • Mentor engineers in Kubernetes/EKS, async programming, multi-agent orchestration, cloud-native development, and responsible AI practices. • Provide input on hiring, onboarding, and talent development to grow AHEAD’s agentic engineering bench. • Partner with Delivery Leads to ensure architecture is executable, scalable, and aligned with timelines. • Champion automation, IaC, CI/CD, model deployment workflows, runbooks, and platform governance. • Lead sprint-level architectural alignment, backlog refinement, retrospectives, and post-incident reviews. • Work with Product Owners and client stakeholders to shape roadmaps, define technical scope, and convert ambiguous problem statements into actionable designs. • Communicate architectural decisions clearly to both technical and business audiences, balancing constraints, risks, and tradeoffs. • Embed platform security, compliance, cost optimization, and data integrity into all architectural decisions.