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Quess IT Solutions is seeking an experienced engineer to lead the development of Agentic AI platforms and full‑stack applications. You will design multi‑agent RAG systems, architect cloud-native solutions, and mentor teams.
You will work with Python backends, FastAPI, Django, Vue.js frontends, and Kubernetes, delivering scalable AI-powered enterprise apps with strong governance and security.
This role combines software engineering, AI engineering, cloud-native architecture, and technical leadership to deliver scalable enterprise solutions across retail and group functions.
The ideal candidate will possess strong expertise in Python backend development, Vue.js frontend engineering, cloud-native architecture, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and Agentic Workflows. The role requires hands-on technical leadership while mentoring engineers and driving engineering excellence across the team.
You will be responsible for building intelligent business applications that seamlessly combine traditional software capabilities with AI-driven automation, decision support, and autonomous agent execution.
Establish best practices for prompt engineering, context management, agent memory, evaluation, monitoring, and governance.
Evaluate emerging AI technologies, models, frameworks, and tools to continuously enhance platform capabilities.
Build mission-critical enterprise applications using Python-based backend frameworks and Vue.js frontend technologies.
Design and develop scalable APIs and microservices supporting AI-powered and Full Stack Application Development traditional business workflows.
Create intuitive and responsive user experiences that seamlessly integrate AI capabilities into business processes.
Develop real-time applications supporting conversational interfaces, workflow automation, and intelligent decision support.
Follow software engineering best practices to deliver scalable, maintainable, and secure solutions.
Design cloud-native architectures that are scalable, resilient, secure, and maintainable.
Define architectural patterns for Agentic AI systems, enterprise AI platforms, and business applications.
Drive adoption of microservices, event-driven architectures, API-first design, and domain-driven design principles.
Lead technical design reviews and architecture discussions.
Establish coding standards, reusable frameworks, engineering accelerators, and development best practices.
Develop and deploy applications on Kubernetes-based infrastructure (AKS preferred).
Design and maintain CI/CD pipelines supporting rapid and reliable software delivery.
Implement observability through monitoring, logging, tracing, alerting, and AI evaluation frameworks.
Ensure applications meet enterprise standards for security, performance, scalability, and reliability.
Collaborate with platform teams to optimize cloud infrastructure and deployment strategies.
Lead and mentor engineering teams to deliver AI-powered products and business applications.
Collaborate with Product Managers, Architects, Data Scientists, and Business Stakeholders throughout the solution lifecycle.
Drive Agile delivery practices and engineering excellence across the team.
Participate in estimation, roadmap planning, technical strategy, and release governance.
Foster a culture of innovation, experimentation, ownership, and continuous learning.