Description

As an AI Agentic Engineer, you will design and optimize AI systems that enhance procurement workflows, leveraging cutting-edge technologies and collaborating with teams to drive intelligent decision-making across the platform.

Requirements

• •Strong professional experience in Python software development
• •Proven experience building AI-driven or agentic systems, preferably with LangGraph or similar frameworks
• •Solid understanding of Large Language Models (LLMs) and their integration with external APIs or structured data
• •Hands-on experience working with LLM providers such as OpenAI, Anthropic, or AWS Bedrock
• •Familiarity with cloud-based deployment and scaling, ideally using AWS services
• •Strong problem-solving skills with a focus on maintainable, efficient, and scalable code
• •Collaborative mindset and comfort working remotely with distributed teams
• •Curiosity, adaptability, and a passion for staying ahead in the evolving world of AI
• •Experience with semantic search technologies (vector databases, embeddings, RAG systems)
• •Strong background in measuring, evaluating, and optimizing AI system performance with clear metrics and benchmarking
• •Experience implementing observability and monitoring solutions for AI systems to track quality and iterate on improvements
• •Experience building or integrating MCP (Model Context Protocol) servers for extending AI capabilities
• •Knowledge of agent-to-agent (A2A) communication patterns and multi-agent system architectures

Tasks

• •Design agentic AI systems
• •Build and optimize procurement workflows
• •Integrate models from OpenAI, Anthropic, and AWS Bedrock
• •Fine-tune AI models for performance
• •Develop software using Python and LangGraph
• •Implement cloud-based solutions using AWS services
• •Collaborate with distributed teams
• •Measure and evaluate AI system performance
• •Implement observability and monitoring for AI systems
• •Explore semantic search technologies

Tools & Technologies

Benefits