GenAI Architect – Fullstack Python, AI Agents, LangGraph, MCP (12+ Years Experience)

About the Role Our client, Predictive Research Inc., is seeking an experienced GenAI Architect with 12+ years of expertise in backend engineering, fullstack system integration, and AI agent orchestration. This is a senior hands-on architect role, blending technical leadership with deep implementation experience. You will be responsible for architecting scalable, context-aware, AI-driven platforms by leveraging Python, LangGraph, MCP , and advanced context engineering strategies. As a GenAI Architect, you will design and integrate intelligent systems powered by LLMs and AI agents, lead the development of adaptive multi-agent workflows, and ensure seamless integration with enterprise-grade backend infrastructures. You will play a critical role in setting architectural direction, mentoring engineering teams, and ensuring successful delivery of production-ready AI solutions. Eligibility: U.S. Citizens & Green Card Holders Only Key Responsibilities Architecture & System Design • Architect end-to-end GenAI platforms combining backend, AI agents, and orchestration workflows. • Define scalable, distributed system architectures that ensure performance, reliability, and compliance. • Establish and enforce best practices for LLM prompt engineering, RAG pipelines, and context management. Backend & Fullstack Development • Architect, implement, and maintain robust backend services and RESTful APIs using Python (FastAPI, Flask, Django). • Lead development of end-to-end applications connecting AI agents with backend services, data sources, and user-facing systems. • Integrate databases (SQL/NoSQL), vector search engines, and distributed systems to power AI workflows. AI Agent Engineering & Orchestration • Design, deploy, and orchestrate autonomous and semi-autonomous AI agents. • Leverage LangGraph for conversational flows, workflow composition, and state management. • Use MCP to coordinate multiple LLMs, models, and agent ecosystems seamlessly. • Integrate AI agents with external APIs, ML models, data pipelines, and enterprise systems. Context Engineering & Optimization • Implement advanced context strategies (session memory, retrieval-augmented generation, personalization). • Optimize prompt design and context handling for precision, adaptability, and real-time awareness. • Continuously evaluate and refine prompt effectiveness and context workflows through experimentation and monitoring. Performance, Security & Compliance • Ensure systems are designed for scalability, high availability, and resilience. • Implement robust monitoring, logging, error handling, and evaluation pipelines. • Enforce data security, privacy, and compliance best practices across AI workflows. Leadership & Collaboration • Partner with data scientists, ML engineers, and product teams to translate business needs into scalable AI solutions. • Mentor engineering teams on AI agent design, orchestration, and fullstack best practices. • Drive cross-functional delivery, ensuring on-time and high-quality implementation of complex AI initiatives. Required Skills & Qualifications • Master’s degree in Computer Science, Engineering, or related field. • 12+ years of professional experience in backend/fullstack engineering with Python. • Expertise in Python frameworks (FastAPI, Flask, Django) and API design. • Proven experience integrating and orchestrating LLMs, AI agents, or multi-agent systems in production. • Hands-on experience with MCP for model composition and multi-agent orchestration. • Proficiency with LangGraph for workflow orchestration and conversational flow design. • Strong knowledge of databases (SQL/NoSQL), vector databases (Pinecone, Weaviate, FAISS, Milvus), and distributed systems. • Experience with cloud infrastructure (AWS, GCP, Azure), containerization (Docker), and CI/CD pipelines. • Excellent problem-solving, leadership, and communication skills. Preferred Qualifications • Experience fine-tuning LLMs, building RAG pipelines, or designing knowledge graph-powered workflows. • Background in information retrieval, search, or enterprise knowledge management systems. • Contributions to open-source projects in AI, agent orchestration, or prompt engineering. • Familiarity with advanced AI security, compliance, and governance frameworks. About Predictive Research Inc. At Predictive Research Inc., we specialize in applying advanced data science, AI, and machine learning to solve complex business challenges. Since our founding in 2011, we have partnered with organizations across industries to deliver predictive modeling, quantitative analytics, and risk assessment solutions that drive smarter decisions. Our expertise spans financial data analytics, regression and simulation, portfolio optimization, consumer and retail analytics, web mining, and large-scale big data applications. Guided by principles inspired by Basaveshwara — devotion, truthfulness, and social responsibility — we are deeply committed to integrity, dedication, and knowledge sharing. By combining technical excellence with ethical responsibility, we empower businesses to unlock the full potential of their data, transforming information into actionable insights for sustainable growth.