Forward Deployment Engineer - Agribusiness/Commodities

Job Description A Fortune 50 company is seeing a Forward Deployed Engineer to bridge the gap between business strategy and AI implementation. This individual will partner with business leaders in the Agribusiness/Commodities industry to understand an automated business need, validate the expected value, and drive the successful implementation of AI initiatives. The ideal candidate combines a deep industry experience, strong engineering skills, and hands-on generative AI experience to drive value and deliver high-impact AI solutions. 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 - 12+ years of combined business and technology experience - Strong business expertise in the Agribusiness/Commodities industry - Salesforce Experience Technical Requirements: - Experience building and deploying AI-driven solutions, including Generative AI and Large Language Models (LLMs) such as OpenAI, Claude, or Gemini. - Familiarity with concepts such as prompt engineering, retrieval-augmented generation (RAG), and agent-based AI architectures. - Strong programming skills in Python and experience working with APIs and system integrations. - Understanding of data platforms, including SQL/NoSQL databases, data modeling, and data pipeline design. - Experience working in cloud environments such as Azure (preferred), AWS, or GCP. - Familiarity with modern application deployment practices, including containerization technologies such as Docker or Kubernetes. - Ability to work with enterprise data sources, including ERP and CRM platforms, and understand how business data is structured, connected, and leveraged to support AI solutions. - Knowledge of enterprise security, governance, and best practices for deploying solutions in large organizations.