We are seeking a Senior AI/ML Engineer to join our AI Engineering team. This is not an academic research position; it's a software engineering role with a specialized focus on Generative AI systems and infrastructure. We need engineers who can architect, build, and deploy production-ready GenAI solutions, including multi-agent systems, prompt marketplaces, and LLM-powered applications. If you're passionate about turning cutting-edge generative AI concepts into robust, scalable enterprise solutions, this role is for you. Responsibilities Design and implement multi-agent systems that leverage multiple LLMs and specialized tools Develop prompt engineering frameworks and infrastructure for enterprise-scale deployment Build and maintain prompt marketplaces/libraries for reusable AI components across the organization Architect and deploy GenAI pipelines and workflows that scale in production environments Containerize GenAI components and integrate them into orchestration systems Design and develop APIs and endpoints for LLM services using frameworks like FastAPI Leverage AWS services including Bedrock, SageMaker, and ECS, Fargate, EC2, and S3 Implement CI/CD practices for GenAI applications using GitHub Actions, Terraform, and Docker Translate high-level business requirements into enterprise-grade GenAI engineering solutions Requirements Bachelor's degree in Software Engineering, Computer Science, or a related field 3+ years of experience in software engineering, AI/ML product engineering, or related fields Proficiency in Python programming Background in GenAI technologies including LLMs, prompt engineering, and multi-agent architectures Hands-on experience with AWS AI services (Bedrock, SageMaker, etc.) and cloud platforms Skills in developing APIs for AI services (e.g., FastAPI) Proven expertise in deployment and scaling of AI/ML models Capability to understand high-level requirements and translate them into robust technical solutions Prompt engineering expertise: understanding how to design, test, and optimize prompts for various use cases System design thinking to architect complex multi-agent systems that combine multiple AI models Strong problem-solving abilities to navigate ambiguity in the rapidly evolving GenAI space Excellent communication skills to explain technical trade-offs and GenAI concepts clearly Proficiency in English at an Upper-Intermediate level (B2) or higher Nice to have Familiarity with RAG architectures Understanding of AgentCore and Strands Knowledge of LangChain/LangGraph Cloud-native development mindset focused on scale, reliability, and maintainability