Python App Architect

Lead Developer / Application Architect (Agentic AI) Job Title: Lead Developer / Application Architect Location: Remote Duration: 11 Months (Contract to Hire) Role Overview We are seeking a highly skilled Lead Developer / Application Architect with deep expertise in Agentic AI systems. This role is focused on hands-on development and architecture of intelligent, autonomous applications capable of decision-making, planning, and execution. The ideal candidate will be a strong engineering-focused professional, not a data scientist, with experience designing and building scalable AI-driven applications using modern frameworks and tools. Key Responsibilities • Design, develop, and deploy Agentic AI systems capable of autonomous reasoning, task execution, and multi-step workflows • Architect scalable and modular AI-driven applications aligned with business requirements • Build and integrate LLM-powered agents, orchestration frameworks, and tool-use pipelines • Develop end-to-end application logic integrating AI agents with APIs, databases, and enterprise systems • Lead development of multi-agent systems including coordination, memory management, and planning mechanisms • Optimize application performance, reliability, and scalability in production environments • Collaborate with cross-functional teams including product, engineering, and DevOps • Ensure code quality, best practices, and maintainability across the development lifecycle • Mentor junior developers and provide technical leadership where required Required Skills & Experience • Strong experience as a Developer or Application Architect (not data-science focused) • Hands-on expertise in Agentic AI / Autonomous AI systems development • Proven experience working with: • LLM frameworks (e.g., LangChain, Semantic Kernel, AutoGen, etc.) • Prompt engineering and agent orchestration • Solid programming skills in Python, JavaScript/TypeScript, or similar languages • Experience in building API-driven and microservices-based applications • Strong understanding of: • AI agent architectures (ReAct, Plan-and-Execute, multi-agent systems) • Memory handling, vector databases, and context management • Experience integrating AI systems with: • External tools and APIs • Enterprise systems and workflows • Familiarity with cloud platforms (Azure, AWS, or Google Cloud Platform) • Strong problem-solving and system design skills Preferred Qualifications • Experience deploying AI applications in production environments • Knowledge of RAG (Retrieval-Augmented Generation) architectures • Familiarity with containerization tools (Docker, Kubernetes) • Exposure to CI/CD pipelines and DevOps practices • Experience building enterprise-grade AI applications