EY-GDS Consulting-AI Enabled Automation-FullStack-Solution Architect
Job description
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EY-Consulting – AI Enabled Automation – Manager - Solution Architect
Experience: 8-10 Years
Job Description:
We are seeking a seasoned Solution Architect with 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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