
High-Performance AI Architect
1 day ago
We are seeking a skilled Solution Architect to design and implement scalable, secure, and reliable AI solutions.
This key technical leader will drive cloud migration, optimize system performance, and guide technical decision-making for AI-powered software solutions.
Responsibilities- Lead AI-Driven Architectural Design & Strategy
Develop architectural designs and strategies for AI-powered software solutions, ensuring scalability, security, and efficiency.
Establish best practices for AI and tech startup development, providing mentorship on system architecture, microservices, and AI deployment strategies.
- Develop & Maintain AI-Ready Backend Services
Build robust backend services using Python (Django, FastAPI) with a focus on AI-driven applications.
Design and implement data pipelines, model inference APIs, and real-time processing frameworks for AI applications.
- AI-Powered Frontend Development
Integrate AI models into web-based platforms, enabling real-time AI interactions and dynamic content generation.
Architect and implement AI-focused microservices, RESTful APIs, and Service-Oriented Architectures (SOA) for startups.
Ensure seamless integration of machine learning models and AI services within distributed systems.
- Containerization & Scalable AI Workflows
Deploy and manage AI applications using Docker and Kubernetes, ensuring scalability and efficient resource utilization.
Automate AI model training, inference, and A/B testing environments for incubated startups.
- Performance Optimization & Real-time AI Solutions
Enhance AI model serving performance, caching mechanisms, and WebSocket-based real-time AI interactions.
Optimize vector databases, embedding-based search, and AI-driven recommendation engines.
Requirements- 10+ years of experience as a Solution Architect, Technical Lead, or similar role.
- Expertise in Python backend development (Django, FastAPI, or equivalent)
- Hands-on experience with AWS cloud services and cloud infrastructure.
- Strong knowledge of Docker, Kubernetes, and DevOps practices.
- Experience with streaming data, WebSockets, and caching for performance optimization.
- CI/CD pipeline expertise using automation tools
- Understanding of microservices, RESTful APIs, and SOA.
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