AI Applications Architect, AI Services

Job Description: • 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. Requirements: • 6+ years designing and delivering cloud-native, event-driven, or distributed architectures at scale (AWS/Azure). • Deep hands-on experience with: • Kubernetes/EKS, Docker, Terraform, and cloud infrastructure patterns • Python, FastAPI, async frameworks, serverless APIs • Vector DBs (Pinecone, Elasticsearch, pgvector) and RAG/LLM integration workflows • Agentic AI frameworks (LangChain, LangGraph, Autogen, CrewAI, LlamaIndex) • Strong knowledge of security, identity, devsecops pipelines, and secrets management in cloud environments. • Proven leadership experience guiding engineering teams, performing code/design reviews, and enforcing architectural best practices. • Excellent communication, stakeholder alignment, and documentation skills. • Experience operating LLMs/SLMs in production (NIMs, Bedrock, OpenAI, Azure OpenAI). • Experience with GPU clusters, inference optimization, or model-serving architectures (Ray, Triton, KServe). • Consulting or client-facing architecture experience. Benefits: • Medical, Dental, and Vision Insurance • 401(k) • Paid company holidays • Paid time off • Paid parental and caregiver leave • Plus more! See benefits for additional details. Apply tot his job