AI Engineer

1. AI Engineering and Architecture Strong proficiency in Python and asynchronous services. Experience developing AI agents, workflows, tool calling, MCP, structured outputs, state, and memory. Solid understanding of Retrieval-Augmented Generation (RAG), embeddings, retrieval, reranking, and source grounding. 2. AWS AI Technologies Hands-on experience with Amazon Bedrock and AgentCore. Familiarity with AgentCore Runtime, Gateway, Memory, Identity, and Observability. Experience with Strands Agents or comparable AI orchestration frameworks. 3. AI Evaluation and Monitoring Experience developing evaluation datasets, regression tests, and adversarial tests. Understanding of task-success metrics, retrieval performance, and AI response quality. Ability to monitor production behaviour, analyse system traces, and identify performance issues. 4. AI Security and Reliability Knowledge of prompt-injection prevention, access controls, tenant isolation, and data privacy. Experience implementing retries, fallbacks, idempotency, and controlled tool execution. Understanding of model versioning, prompt versioning, and quality-based release processes. 5. AI-Assisted Development Strong practical experience using Claude Code and OpenAI Codex. Ability to manage AI coding agents through clear instructions, context management, and scoped tasks. Capable of reviewing, testing, and validating AI-generated code. Additional Advantage: Experience working with local or open-weight AI models, model serving, quantisation, hardware constraints, and self-hosted inference.