Senior Python & AI Engineer Needed for Intelligent Workflow Automation & Model Integration

We are looking for a skilled, autonomous, and performance-driven Python Developer with deep expertise in Artificial Intelligence and workflow automation. The goal of this project is to architect, build, and optimize intelligent backend services that leverage cutting-edge Large Language Models (LLMs) and automated data-processing pipelines. You will have end-to-end ownership of the backend AI architecture, ensuring that our intelligent workflows are scalable, deterministic, and securely integrated with our core application ecosystems. Key Responsibilities AI Integration & Automation: Design, build, and maintain robust Python-based microservices and intelligent agents leveraging models like OpenAI, Claude, or open-source alternatives. Workflow Optimization: Implement automated decision-making engines, multi-agent frameworks, or background task queues to streamline complex data pipelines and repetitive business processes. API Development: Architect and deploy secure, high-performance RESTful APIs (using frameworks like FastAPI or Flask) to expose AI capabilities to frontend services and third-party consumers. Data & Performance Tuning: Write highly optimized, clean Python code; manage relational or vector databases (e.g., PostgreSQL, Pinecone, ChromaDB); and eliminate operational bottlenecks. Cloud Deployment: Package and deploy applications using modern cloud environments (AWS or Azure) utilizing CI/CD pipelines, Docker containerization, and serverless compute functions. Required Technical Skills Backend: Strong proficiency in Python (3.10+), asynchronous programming, and clean code practices (SOLID principles). AI & LLMs: Hands-on experience with API integration of foundational models (OpenAI, Anthropic Claude), prompt engineering architectures, and framework ecosystems (e.g., LangChain, LlamaIndex). APIs & Core Tech: Experience constructing robust RESTful Web APIs, data validation layers, and integrating external microservices. Database: Solid understanding of database design, query optimization, and structured schemas (SQL/NoSQL) alongside familiarity with vector embeddings. DevOps/Tools: Full proficiency with Git, Docker, and setting up automated CI/CD deployment pipelines. Nice-to-Have Skills Experience implementing AI-driven sentiment analysis, automated support ticket classification, or intelligent itinerary/agent routing tools. Familiarity with data-science libraries (NumPy, Pandas) or building multi-tenant SaaS platforms.