Senior AI/ML Engineer (AWS, Docker)

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