AI Architect – Agentic & Generative AI

ob Description: As AI Architect – Agentic & Generative AI, you will be responsible for defining, building, and scaling enterprise-grade agentic AI architecture on AWS. This role focuses on establishing frameworks, patterns, and guardrails that enable safe, reliable, and cost-efficient AI solutions, leveraging Amazon Bedrock (Agents, Knowledge Bases, Guardrails, Flows) and Claude models. You will collaborate with cross-functional teams in product, engineering, data, and security to deliver next-generation AI capabilities — including retrieval-augmented generation (RAG), multi-agent orchestration, and governed AI operations — driving measurable business impact through intelligent automation and decision-making systems. Responsibilities Define and evolve the enterprise agentic AI architecture, establishing reusable frameworks and standards for RAG, tool/function calling, and multi-agent orchestration. Design and implement AI solutions using Amazon Bedrock and integrate with core AWS services (Lambda, Step Functions, EventBridge, ECS/EKS, S3, Aurora, OpenSearch, DynamoDB). Drive adoption of agentic AI patterns — planning, memory, and human-in-the-loop — ensuring alignment with enterprise security and compliance frameworks. Guide model selection and optimization (Claude family and Bedrock models), including prompt schema design, adapters, and fine-tuning strategies. Implement advanced RAG pipelines with optimized chunking, reranking, grounding, and hybrid/vector retrieval using OpenSearch and pgvector. Apply Guardrails and data-governance controls (IAM/ABAC, KMS, private networking) to ensure privacy, PII protection, and compliant operations. Establish observability and reliability frameworks — including evaluation pipelines, tracing, cost metrics, fallbacks, and A/B testing. Collaborate with platform and DevOps teams to enable governed AWS landing zones, CI/CD automation, and environment management for AI workloads. Publish architecture blueprints, starter kits, and best-practice guides for AI engineers and developers. Mentor engineering teams and contribute to hiring, training, and AI community enablement initiatives. Research and assess emerging AWS and open-source agentic tools, proposing pragmatic adoption strategies. Required Skills & Experience 8+ years designing and implementing large-scale distributed or cloud systems (including 4+ years on AWS). 2+ years building AI/ML or generative AI solutions in production environments. Hands-on experience with Amazon Bedrock (Agents, Knowledge Bases, Guardrails) and Claude models. Deep understanding of RAG design, hybrid/vector search (OpenSearch, pgvector), grounding, and citation techniques. Proficiency in Python (preferred) or similar modern programming languages. Solid grasp of AWS orchestration services (Lambda, Step Functions, EventBridge) and CI/CD practices. Applied knowledge of AI governance, security, and observability (IAM, KMS, Guardrails, evaluation, tracing). Excellent communication and architectural documentation skills. Preferred Qualifications Expertise in Agentic AI systems, including multi-agent workflows, tool/function calling, and memory architectures. Experience with LangChain, LangGraph, or similar orchestration frameworks. Advanced prompt design, RAG optimization, and model customization experience. AWS Certifications – Solutions Architect (Professional) or Machine Learning Specialty.