AI Engineer

Compunnel

$120K — $145K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in software development or AI engineering.
  • Bachelor's or Master's in Computer Science or related field.
  • Strong experience with AI/ML technologies.
  • Hands-on expertise in LangGraph workflows.
  • Proficiency with IBM Watsonx Orchestrate for automation.
  • Experience with Google Vertex AI capabilities.
  • Proficiency in Java and Python.

Responsibilities

  • Design and develop AI-driven automation solutions.
  • Build workflows using LangGraph with advanced features.
  • Develop process automation utilizing IBM Watsonx Orchestrate.
  • Leverage Google Vertex AI for AI advancements.
  • Apply machine learning principles in solution development.
  • Develop NLP solutions for human language interaction.
  • Implement collaborative multi-agent systems.

Benefits

  • Remote work flexibility.
  • Access to ongoing professional development.
  • Collaborative team environment.
  • Cutting-edge technology and tools.
  • Opportunities for innovation in AI solutions.
Full Job Description
Job Summary:

Seeking a Senior Software Developer with 5+ years of experience and deep hands-on expertise in building AI-driven and agentic automation solutions. The ideal candidate will have strong experience with LangGraph, IBM Watsonx Orchestrate, and Google Vertex AI, with the ability to design scalable services incorporating advanced reasoning, workflow orchestration, multi-agent systems, and AI/ML capabilities.

Key Responsibilities:
• Design and develop AI-driven and agentic automation solutions using modern AI technologies.
• Build agentic workflows using LangGraph, including graphs, tool nodes, memory/state management, and streaming agents.
• Develop AI-powered process automation using IBM Watsonx Orchestrate, including skills, connectors, and process automation.
• Leverage Google Vertex AI, including Gemini, Retrieval-Augmented Generation (RAG), Vector Search, embeddings, and AI safety capabilities.
• Apply machine learning and deep learning concepts, including AI models, neural networks, and reinforcement learning.
• Develop natural language processing (NLP) solutions that interpret and generate human language.
• Design and implement multi-agent systems where AI agents collaborate, negotiate, and operate independently.
• Deploy AI solutions and models using cloud platforms such as AWS, Google Cloud, or Azure.
• Design AI-driven Robotic Process Automation (RPA) solutions to automate repetitive business processes.
• Develop and maintain applications using Java and Python.
• Analyze complex AI outputs, troubleshoot unexpected AI behavior, and optimize model and application performance.
• Apply ethical reasoning to help ensure AI applications support responsible and unbiased decision-making.
• Collaborate with cross-functional teams to integrate AI systems into business processes and applications.

Required Qualifications:
• 5+ years of professional software development or relevant AI engineering experience.
• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field.
• Strong experience with AI/ML.
• Strong hands-on experience with LangGraph, including graphs, tool nodes, memory/state, and streaming agents.
• Strong hands-on experience with IBM Watsonx Orchestrate, including skills, connectors, and process automation.
• Strong hands-on experience with Google Vertex AI, including Gemini, RAG, Vector Search, embeddings, and safety capabilities.
• Proficiency in Java.
• Proficiency in Python.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure for AI deployment.
• Experience with NLP, multi-agent systems, AI automation, or related technologies.

Preferred Qualifications:
• Experience with IBM Watsonx Platform, including Watsonx Assistant, AI, and Orchestrate.
• Experience with chatbot development.
• Experience designing scalable AI services and agentic automation solutions.
• Strong critical-thinking and problem-solving skills, particularly when evaluating AI outputs and handling complex situations under uncertainty.

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