Lead AI Engineer: Automation & Multi-Agent Systems

Job Summary Lead AI Engineer will be responsible for building AI-driven and agentic automation solutions. This role requires deep expertise in designing scalable services that incorporate advanced reasoning, workflow orchestration, and multi-agent systems, with ideal candidates having experience in LangGraph, IBM Watsonx Orchestrate, and Google Vertex AI. Key Responsibilities Build AI driven and agentic automation solutions. Design scalable services incorporating advanced reasoning, workflow orchestration, and multi-agent systems. Develop AI systems that interpret and generate human language (NLP). Understand and implement multi-agent systems where AI agents collaborate and operate independently. Deploy AI models using cloud platforms (AWS, Google Cloud, or Azure). Design AI-driven bots for repetitive task automation (RPA). Utilize LangGraph for graphs, tool-nodes, memory/state, and streaming agents. Implement IBM Watsonx Orchestrate for skills, connectors, and process automation. Leverage Google Vertex AI for Gemini, RAG, Vector Search, embeddings, and safety features. Work with vector databases such as PGVector, Vertex Matching Engine, and Pinecone. Implement eventing patterns using Kafka or Pub/Sub. Utilize observability stacks including OpenTelemetry, Prometheus/Grafana, and Elk/Cloud Logging. Employ infrastructure-as-code principles with tools like Terraform. Integrate with CI/CD pipelines using GitHub Actions and Cloud Build. Apply critical thinking to analyze AI outputs and improve models. Ensure ethical and unbiased decision-making in AI applications. Solve problems related to unexpected AI behaviors and optimize performance. Collaborate with cross-functional teams to integrate AI systems. Required Qualifications Bachelor's or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field. 5+ years of experience with Java. 5+ years of strong experience in AI/ML. Experience with LangGraph. Experience with IBM Watsonx Orchestrate. Experience with Google Vertex AI. Knowledge of vector databases (PGVector, Vertex Matching Engine, Pinecone). Familiarity with Kafka or Pub/Sub eventing patterns. Familiarity with observability stacks (OpenTelemetry, Prometheus/Grafana, Elk/Cloud Logging). Familiarity with infrastructure-as-code (Terraform). Familiarity with GitHub Actions and Cloud Build. Understanding of AI models, neural networks, and reinforcement learning. Preferred Qualifications Experience with WatsonX Platform (Assistant, AI, Orchestrate etc). Chatbot development experience. #J-18808-Ljbffr Compunnel, Inc.