AI Engineer

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 4 -6 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 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 Multi agent workflow deployment experience Understanding of common LLM failure modes such as hallucinations and grounding issues Ability to evaluate LLM responses for accuracy, relevance, and safety Experience on AI/ML and computer vision is preferred Experience on pre sales on AI such as RFP response , Solution Architecture design , BOQ ( Hardwares and Softwares ) is required Experience on product and solutions is preferred. 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 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 Professiona, Machine Learning, or Data Science Prior experience in enterprise or cloud-native environments