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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI System Engineer - **Company:** INNOVATIVE CONSULTING - **Location:** Atlanta, GA, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Computing, Data Visualization, Distributed Systems, Django Web Framework, Graph Database, Iterative and Incremental Development, Information Retrieval, Python (Programming Language), Machine Learning, NoSQL, Open Source Technology, Scrum Methodology, Software Architecture, Systems Development Life Cycle, Search Technologies, SQL Databases, Systems Integration, Web Application Frameworks, Workflow Management Systems, Google Cloud, ReactJS, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Reliability of Systems, Generative AI, Backend, Fastapi, Vue.js, Containerization, AngularJS, Kubernetes, Low Latency, Machine Learning Operations, Front End Software Development, GPT, Docker, Web Api - **Published:** September 15, 2026 - **Apply:** https://www.disabledperson.com/jobs/75188265-ai-system-engineer ## About the Role We are seeking versatile and highly skilled AI Systems Engineer with deep expertise in Fullstack Python development, intelligent agent orchestration, and advanced context engineering. This role is central to building next-generation AI-powered applications that leverage large language models (LLMs), multi-agent workflows, and dynamic context management. You will architect and integrate scalable systems using frameworks like LangGraph and MCP, while collaborating across disciplines to deliver adaptive, intelligent solutions., 1. Strong experience with Fullstack Python development (FastAPI, Flask, Django; SQL/NoSQL databases). 2. Proven expertise in prompt engineering and context-aware LLM integration (OpenAI, Anthropic, open-source models). 3. Hands-on experience with LangGraph and MCP for agent orchestration and workflow design. 4. Familiarity with vector search, RAG pipelines, and session/context management strategies. 5. Experience integrating AI agents into production systems with cloud infrastructure (AWS, GCP, Azure). 6. Proficiency with containerization (Docker), CI/CD pipelines, and scalable distributed systems. 7. Excellent problem-solving, communication, and collaboration skills. Preferred Qualifications 1. Background in information retrieval, knowledge graphs, or search systems. 2. Experience with front-end development and data visualization tools. 3. Contributions to open-source AI, agent, or LLM frameworks. 4. Familiarity with advanced ML model serving and orchestration platforms ## Description Prompt & Context Engineering 2. Design and optimize prompts for LLMs to ensure accurate, contextually rich outputs across diverse use cases. 3. Architect dynamic context management systems including session memory, retrieval-augmented generation (RAG), and user personalization. Agent Integration & Orchestration 5. Develop and deploy autonomous and semi-autonomous AI agents using LangGraph and MCP. 6. Coordinate multi-agent workflows, manage state transitions, and ensure seamless model interoperability. Fullstack System Development 1. Build robust backend services and APIs using Python frameworks (FastAPI, Flask, Django). 2. Develop front-end interfaces using modern JS frameworks (React, Vue, Angular) to support end-to-end user experiences. System Integration 1. Connect agents with external data sources, vector databases, third-party APIs, and ML models. 2. Implement scalable pipelines for knowledge retrieval, model serving, and real-time interaction. Evaluation & Optimization 1. Establish testing, monitoring, and evaluation pipelines to continuously improve agent performance and context handling. 2. Optimize system reliability, latency, and scalability across cloud environments. Collaboration & Delivery Work cross-functionally with product managers, data scientists, and ML engineers to define requirements and deliver production-grade solutions. Contribute to architectural decisions, sprint planning, and iterative development cycles. ## Related Videos - [Livecoding with AI](https://www.wearedevelopers.com/videos/1201-livecoding-with-ai) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Lessons learned from building a thriving Vue.js SaaS application](https://www.wearedevelopers.com/videos/1666-lessons-learned-from-building-a-thriving-vue-js-saas-application) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) ## 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) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care)