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EY EY-GDS Consulting-AI Enabled Automation-FullStack-Solution Architect 
India, Kerala, Kochi 
57694672

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8-10 Years

Job Description:

We are seeking a seasonedwith over 8 years of experience in full stack development and AI-driven solution design. This role requires a strong technical leader who can architect, guide, and contribute to the development of scalable web applications and AI-powered systems. The ideal candidate will have deep expertise in Python, .NET, modern front-end frameworks, and hands-on experience with Generative AI technologies.


Key Responsibilities:

  • Architect end-to-end solutions across full stack technologies (Python, .NET, JavaScript frameworks) and AI components.
  • Lead and mentor development teams working on full stack and Generative AI projects.
  • Collaborate with stakeholders to define technical requirements, system architecture, and delivery roadmaps.
  • Design and implement scalable, secure, and high-performance applications.
  • Integrate Large Language Models (LLMs) and other Generative AI capabilities into enterprise applications.
  • Ensure adherence to best practices in coding, testing, deployment, and DevOps.
  • Review code, provide technical guidance, and drive continuous improvement.
  • Stay current with emerging technologies and evaluate their applicability to business needs.

Required Qualifications:

  • 8+ years of experience in software development with a strong foundation in full stack technologies.
  • Proficiency in Python (Django, Flask) and .NET (ASP.NET, .NET Core).
  • Strong front-end development skills using React, Angular, or Vue.js.
  • Experience designing and deploying RESTful APIs and microservices.
  • Hands-on experience with Generative AI tools and frameworks (e.g., OpenAI, Hugging Face, LangChain).
  • Solid understanding of cloud platforms (AWS, Azure, or GCP).
  • Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
  • Strong problem-solving, communication, and leadership skills.

Preferred Qualifications:

  • Experience with prompt engineering, fine-tuning LLMs, or Retrieval-Augmented Generation (RAG) systems.
  • Familiarity with MLOps practices and AI model lifecycle management.
  • Exposure to enterprise architecture frameworks and solution design patterns.
  • Background in mentoring or managing cross-functional technical teams.

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