Job Description

Technology & Architecture Design and develop the implementation of scalable, secure, and resilient backend systems using FastAPI, Flask, Django, and microservices. Drive adoption of cloud-native and DevOps practices (CI/CD pipelines, container orchestration, observability, monitoring). Integration of LLM/Generative AI capabilities (RAG pipelines, vector databases, agentic-AI frameworks) into backend services. Ensure system reliability, data integrity, and compliance with security and privacy standards. Well versed with Azure and/or AWS. Leadership & Communication Manage and mentor a team of backend and AI engineers. Act as a bridge between engineering, product, and business teams, clearly translating technical concepts into business impact. Represent engineering in stakeholder discussions, ensuring alignment of priorities, risks, and deliverables. Foster a culture of collaboration, accountability, and innovation across teams. AI & Innovation Design, develop, and deploy AI solutions using Agentic and Generative AI frameworks by leveraging tools such as LangChain, Azure OpenAI, HuggingFace. Build and maintain scalable applications using Python and Node.js. Guide prompt engineering, fine-tuning, and AI-powered automation to improve system intelligence and decision support. Stay updated on emerging technologies (Agentic AI, autonomous systems, advanced data pipelines) and drive relevant adoption. Delivery & Operational Excellence Ensure backend and AI projects are delivered on time and with high quality. Set and enforce engineering standards: coding best-practices, architecture reviews, documentation, and code quality checks. Proactively identify and resolve system bottlenecks, scalability challenges, and performance issues. Implement metrics-driven engineering KPIs (uptime, latency, throughput, model performance) for continuous improvement.