AI Architect

Job Requirements

8+ years of experience in software development and technical architecture, with strong hands-on experience in Python.

Expert-level knowledge of Python, object-oriented programming, design patterns, data structures, and software engineering principles.

Strong experience designing enterprise applications, microservices, REST APIs, and distributed systems.

Strong understanding of AI/ML concepts, algorithms, model lifecycle, model evaluation, and AI/ML application architecture.

Strong experience in GenAI, LLMs, RAG, embeddings, and vector databases

Design end-to-end solution architectures embedding Generative AI components (LLMs, RAG pipelines, prompt engineering, AI agents) into core enterprise systems.

Establish architecture standards, design principles, and governance frameworks for microservices, APIs, and cloud-native application design.

Model application, data, and integration architectures to ensure performance, scalability, security, and maintainability.

Evaluate and select GenAI platforms, frameworks, and tooling based on architectural fit, technical feasibility, and long-term scalability.

Conduct architecture reviews and technical design assessments to ensure compliance with enterprise design standards

Hands-on experience with PyTorch, TensorFlow, Scikit-learn, or equivalent AI/ML frameworks.

Experience with Python frameworks such as FastAPI, Flask, or Django.

Strong knowledge of SQL, databases, data processing, and data integration.

Experience designing and deploying solutions on AWS, Azure, or GCP.

Understanding of MLOps, CI/CD, Docker, Kubernetes, model deployment, and monitoring.

Experience integrating AI/ML capabilities with enterprise applications using APIs and microservices

Work Experience

10-15Years