Job Description We are seeking an Agentic AI Engineer to join a clients AI Center of Excellence. This hands-on role involves designing, developing, testing, and deploying AI agents that can perceive their environment, make decisions, and take autonomous actions. You’ll collaborate with AI Architects, Data Scientists, and business stakeholders to build innovative solutions for areas like supply chain optimization, intelligent automation, and enhanced customer/vendor experiences. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements Education & Experience: Bachelor’s or Master’s in Computer Science, AI, ML, or related field 3–5+ years in software engineering with AI/ML focus Technical Skills: Strong Python skills and AI/ML libraries (e.g., scikit-learn, Pandas, NumPy, Hugging Face) Experience with agentic AI frameworks (e.g., Google ADK, LangChain, AutoGen, CrewAI) Working with LLMs for NLU, reasoning, and function calling (e.g., GPT, Claude, Gemini) API development/integration (REST, gRPC) Cloud platforms (GCP, AWS, Azure) and AI services (Vertex AI) CI/CD, Git, software engineering best practices Core Competencies: Deployment and operationalization of models/agents Problem-solving, debugging, and collaboration in agile environments Strong communication skills Experience deploying AI solutions in production Familiarity with MLOps/LLMOps practices Containerization (Docker, Kubernetes) Knowledge of vector databases and RAG systems Basic data engineering concepts Automated testing frameworks Open-source contributions Domain knowledge in supply chain, logistics, or enterprise automation