Job Summary
The AI/ML Architect will lead the architecture and delivery of enterprise AI/ML solutions on AWS, with a focus on Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), and Machine Learning. The role will translate complex business requirements into scalable, secure, and production-ready AI architectures while providing hands-on technical leadership across architecture, design, implementation, and governance. This customer-facing role will collaborate directly with senior client stakeholders, business teams, data teams, security, compliance, and engineering teams and will provide technical guidance throughout the AWS AI program.
Key Responsibilities
• Lead discovery sessions with business stakeholders, product owners, data teams, security, compliance, and engineering teams.
• Translate complex business requirements into implementable AI/ML solutions and technical architectures.
• Develop HLDs, LLDs, Technical Design Documents, architecture decision records, reference implementations, and production-ready designs.
• Design scalable Generative AI, Agentic AI, RAG, and Machine Learning solutions on AWS.
• Architect solutions using Amazon Bedrock, SageMaker, Knowledge Bases, AgentCore/Agents, AWS Strands, LangGraph, LangChain, CrewAI, and related technologies.
• Define RAG architecture covering ingestion, chunking, embeddings, vector and hybrid search, retrieval, reranking, grounding, citations, permissions, and evaluation.
• Define security, privacy, responsible AI, observability, resilience, scalability, and cost controls for AI/ML solutions.
• Build Python proof-of-concepts and technical spikes to validate architecture, model quality, AWS services, integrations, latency, and cost.
• Provide hands-on technical leadership, review code and designs, and troubleshoot complex AI/ML and AWS issues.
• Present architecture, technical trade-offs, risks, and recommendations to senior client executives and business and technical stakeholders.
• Lead design reviews, production-readiness reviews, technical sign-offs, and technical governance activities.
• Mentor engineering teams and ensure solutions are implemented in accordance with the defined architecture.
Required Qualifications
• 15-20+ years of overall professional experience, with strong recent experience in AI/ML architecture and AWS.
• Strong enterprise architecture and client-facing consulting experience.
• Strong hands-on experience with Generative AI, LLMs, RAG, Agentic AI, and Machine Learning.
• Strong AWS experience, including Bedrock, SageMaker, Knowledge Bases, AgentCore/Agents, Lambda, Step Functions, ECS/Fargate, EKS, S3, OpenSearch, API Gateway, and EventBridge.
• Experience with LangChain, LangGraph, CrewAI, AWS Strands Agents, or equivalent technologies.
• Strong Python experience with the ability to develop proof-of-concepts and technical solutions.
• Experience developing REST APIs and implementing event-driven architectures.
• Strong understanding of vector databases and vector search technologies.
• Experience with AI evaluation, guardrails, and responsible AI practices.
• Strong understanding of AWS IAM, KMS, Secrets Manager, VPC, and CloudWatch.
• Experience with CI/CD and Infrastructure-as-Code technologies such as Terraform, AWS CDK, or CloudFormation.
• Strong understanding of enterprise security, privacy, observability, resilience, scalability, and cost management.
• Strong communication, consulting, leadership, and stakeholder-management skills.
• Ability to communicate complex technical concepts, architecture decisions, trade-offs, risks, and recommendations to senior stakeholders and business teams.
