AI/ML Architect – AWS

This is a customer-facing role supporting a large AWS AI program. The selected resource will interact directly with senior client stakeholders and business teams.

Experience: 15–20+ years of overall experience, with strong recent experience in AI/ML architecture and AWS.

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, 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 including ingestion, chunking, embeddings, vector/hybrid search, retrieval, reranking, grounding, citations, permissions, and evaluation.
Define security, privacy, responsible AI, observability, resilience, scalability, and cost controls.
Build Python POCs and technical spikes to validate architecture, model quality, AWS services, integrations, latency, and cost.
Provide hands-on technical leadership, review code/designs, and troubleshoot complex AI/ML and AWS issues.
Present architecture, technical trade-offs, risks, and recommendations to senior client executives and business/technical stakeholders.
Lead design reviews, production-readiness reviews, technical sign-offs, and technical governance.
Mentor engineering teams and ensure the architecture is implemented as intended.