GenAI Agent Developer

Job description

**Preferred candidate profile** - Troubleshooting Skills 5 years: B1 - Systematic debugging - Log analysis - Performance profiling - Incident response - Prompt Engineering – 2 years: - Prompt Design: effective prompts for different personas, tasks, schema & models - Few-shot & Zero-shot Learning: guide model behaviors - Building AI Agents 2 years: - Agent Frameworks: langchain, autogen, crewai, MCP, etc. - Memory & Context Management: long-term memory, RAG - Tool Use & Planning: Integrating external tools (API/DB), multi-step reasoning, task decomposition - State management: goal tracking, actions, outcomes - LLM Integration: using common open and closed models (OpenAI, Gemini, Anthropic, Llama, etc.) - Evaluation & safety: testing agent behavior, fail-safes, ethical constraints - Security: input sanitization, sensitive data handling, prompt injection projection, scoped permissions, logging, rate limiting - AWS Public Cloud Skills 3-5 years: - Core services: EC2, S3, Terraform/CloudFormation, Lambda, DynamoDB - AI services: Bedrock, Bedrock Agents - Security: IAM policies, roles, KMS, secrets manager - Database Skills 3-5 years: - SQL mastery: joins, indexing, query optimization - Data modeling: normalization, denormalization, er diagrams, schema design - Performance tuning: Query plans, caching strategies - Programming Languages 3-5 years: - Go - Python - Java - Terraform (nice to have)