Principle AI Architect Education • • Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field • Strong academic foundation in statistics, probability, and LLM and Agentic AI and AWS Bedrock Experience • Optional skills Machine Learning and Neural networks • 12- 18 years of professional experience in LLM, Agentic AI • All aspects of BEDROCK, use of security APIs from AWS, Dynamo DB, Experience in Claude LLMs • Experience working on end-to-end Bedrock workflows • Ability to translate business and product requirements into data-driven solutions Generative AI & LLMs & AI/ML • • Hands-on experience developing LLM-powered applications using Amazon Bedrock or similar platforms • Experience building or contributing to Retrieval-Augmented Generation (RAG) pipelines, including: • Document ingestion and chunking • Embedding generation • Similarity search using vector databases • Practical knowledge of prompt engineering, prompt tuning, and output evaluation • Understanding of common LLM failure modes such as hallucinations and grounding issues • Ability to evaluate LLM responses for accuracy, relevance, and safety • AI/ML model actual Experience in model building • Solution Architecture and Presales / GTM experience on AI/ML/LLM/Agentic AI. Agentic AI (Growing Expertise) • • Exposure to Agentic AI concepts and frameworks such as AgentCore • Experience implementing: • Simple Autonomous agents or workflows • Multi-step reasoning with predefined tools • Familiarity with tool-calling, agent orchestration, and workflow automation • Understanding the importance of: • Guardrails • Human-in-the-loop mechanisms • Logging and observability for agent behavior Cloud Platform: • • • Working knowledge of key AWS services, including: • S3, Lambda, Redshift, IAM, S3, AWS WAF, Query handler , Lambda Professional & Collaboration Skills • • Team mentoring and Solution Governance • Strong Python programming skills and experience working with APIs • Ability to work effectively in cross-functional teams (product, engineering, analytics) • Willingness to learn quickly in a fast-evolving AI landscape ( flexibility and learning attitude ) • Comfortable taking technical guidance and implementing feedback • Clear communication of findings, limitations, and model behavior to non-technical stakeholders Nice to Have • • • Initial exposure to AI governance, compliance, or ethical AI practices • Experience with monitoring LLM outputs and basic evaluation frameworks • Certifications in AWS Bedrock Gen AI Developer Professional , Azure and GCP Machine Learning, or Data Science