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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Software Engineer - **Company:** Insight Global - **Location:** Orangeburg, SC, United States - **Experience:** Expert - **Salary:** $150,000.0 - $185,000.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, ARM Architecture, Microsoft Azure, Business Software, Cloud Computing, Collaborative Software, Continuous Integration, Information Engineering, Data Security, Middleware, Graph Database, Supervisory Control and Data Acquisition (SCADA), Information Extraction, Information Retrieval, Python (Programming Language), Machine Learning, Microsoft Copilot, Salesforce.Com, Search Technologies, Software Construction, Software Engineering, Systems Integration, Workflow Management Systems, Enterprise Data Management, Enterprise Software Applications, Chatbots, LangChain, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, IT Architecture, Model Validation, Generative AI, Backend, Agentic-AI, Git, Data Layers, Event Driven Architecture, AI Platforms, Kubernetes, Information Technology, Deployment Automation, CrewAI, AutoGen, Data Management, Prompt Frameworks, Virtual Agents, Api Design, Model Explainability, Restful APIs, Semantic Kernel, Databricks - **Published:** October 2, 2026 - **Apply:** https://dejobs.org/x/x/B7B58132BB6641DAB07DD9638EC91958/job/ ## About the Role * Bachelor's degree in Computer Science, Software Engineering, Data Science, AI, or related technical discipline. * 6+ years of experience in software engineering, AI engineering, machine learning engineering, or related technical roles. * Strong proficiency in Python and experience developing APIs, backend services, and automation frameworks. * Hands-on experience with LLMs, prompt engineering, AI agents, RAG architectures, and vector databases/search technologies. * Experience with modern AI frameworks and orchestration tools (LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar). * Experience integrating enterprise systems using REST APIs, event-driven architectures, or middleware platforms. * Familiarity with cloud and data platforms such as Snowflake, Azure, AWS, Databricks, or similar ecosystems * Strong understanding of software engineering best practices including Git, CI/CD, testing, monitoring, and deployment pipelines. * Excellent communication and cross-functional collaboration skills. * Master's degree in Computer Science, Software Engineering, Data Science, AI, or related technical discipline. * Experience with Snowflake Cortex, Snowpark, AI agent frameworks, or enterprise AI platforms * Experience with enterprise knowledge graphs, semantic layers, or document intelligence systems. * Familiarity with MCP architectures, AI orchestration platforms, or multi-agent systems. * Experience implementing AI governance, observability, and model evaluation frameworks. * Experience supporting AI deployments in manufacturing or industrial environments. * Demonstrated ability to operationalize AI solutions from prototype through enterprise deployment. ## Description Insight Global is hiring an AI Engineer to design, develop, and operationalize enterprise AI solutions that enable intelligent automation, conversational AI, AI agents, and scalable AI-powered workflows across manufacturing and enterprise business functions. This role focuses on transforming AI concepts into production-ready systems by integrating Large Language Models (LLMs), AI agents, enterprise data platforms, APIs, orchestration frameworks, and business applications. The AI Engineer will work closely with data scientists, data engineering, enterprise architecture, manufacturing teams, and business stakeholders to deploy scalable AI capabilities aligned with enterprise AI strategy. The ideal candidate possesses strong software engineering and AI integration experience, including hands-on expertise with AI orchestration frameworks, APIs, vector search, retrieval-augmented generation (RAG), and enterprise system integration. This individual will play a critical role in establishing enterprise AI standards, reusable AI patterns, and operational AI platforms that support future AI scale across the organization. Responsibilities: - Design, develop, and deploy enterprise AI applications, AI agents, copilots, and intelligent workflow solutions across manufacturing and corporate domains. - Build and maintain AI orchestration pipelines utilizing LLMs, retrieval-augmented generation (RAG), vector search, prompt frameworks, and agent-based architectures. - Develop scalable AI integration patterns between enterprise platforms such as Snowflake, Salesforce, ERP systems, SCADA/OT systems, document repositories, and collaboration platforms. - Collaborate with data scientists and business stakeholders to operationalize machine learning and generative AI solutions into production environments. - Design APIs, middleware, and integration services supporting AI-driven automation and cross-platform communication. - Develop and optimize semantic search, enterprise knowledge retrieval, and conversational AI capabilities. - Support the implementation of AI governance, security, observability, model evaluation, and human-in-the-loop approval processes. - Drive enterprise AI architecture strategy and standards, partnering across teams to define approaches for AI platforms, orchestration, deployment, and lifecycle management. - Data Security in workflows, Prompt injection Mitigation, Model explainability (where required) - Monitor AI application performance, cost efficiency, reliability, and user adoption metrics. - Stay current on emerging AI technologies, frameworks, and industry trends, and evaluate their applicability to enterprise AI initiatives. - Understand and optimize consumption and cost patterns ## Related Videos - [Building Scalable Multi-Agentic AI Systems in Java: Orchestrating Agents with Event-Driven Approach](https://www.wearedevelopers.com/videos/1967-building-scalable-multi-agentic-ai-systems-in-java-orchestrating-agents-with-event-driven-approach) - [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [Rethinking Workflows in the Agentic Era](https://www.wearedevelopers.com/videos/1540-rethinking-workflows-in-the-agentic-era) - [What is Agent Memory? - William Lyon](https://www.wearedevelopers.com/videos/1846-what-is-agent-memory-william-lyon) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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