Artificial Intelligence

• 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.

AI Applications Architect, AI Services

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Patent Engineer – AI/ML, Kernel & High-Performance Compute

AI Catalyst

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AI Intern