Key Responsibilities

- Define enterprise architecture patterns for Generative AI, including Retrieval-Augmented Generation (RAG), AI agents, orchestration frameworks, and API/microservices-based integrations.
- Design and implement enterprise-scale GenAI architectures using LLMs, vector databases, AI agents, and orchestration frameworks.
- Establish reusable architecture patterns, reference frameworks, and best practices for AI platform development.
- Lead long-term AI and data strategy aligned with business objectives.
- Design scalable, secure, and highly available AI solutions across AWS and Azure cloud platforms.
- Define integration strategies using microservices, REST APIs, and event-driven architectures.
- Conduct architecture reviews, risk assessments, and ensure adherence to enterprise architecture standards.
- Define AI security, governance, access control, and compliance frameworks.
- Partner with engineering, product, business, and executive stakeholders to drive AI initiatives.
- Mentor architects and engineering teams on AI architecture, design patterns, and best practices.

Required Skills & Qualifications

- 10+ years of experience in Software Architecture.




- 5+ years of hands-on experience in AI/ML Architecture.
- Strong experience designing enterprise-scale AI and Generative AI solutions.
- Expertise in Machine Learning frameworks:
- TensorFlow
- PyTorch
- Scikit-learn

- Hands-on experience with MLOps tools:

- Kubeflow
- MLflow
- Apache Airflow
- Docker
- Kubernetes

- Deep expertise in cloud platforms:

- AWS
- Microsoft Azure

- Strong experience with:

- Retrieval-Augmented Generation (RAG)
- Large Language Models (LLMs)
- Vector Databases
- AI Agent Frameworks
- LLM Orchestration

- Experience designing microservices and API-driven architectures.
- Solid understanding of AI security, governance, access management, and compliance.
- Excellent stakeholder management, leadership, and communication skills.
- Experience mentoring technical teams and influencing architectural decisions.

Good to Have

- Experience with Databricks, Dataiku, or similar AI/ML platforms.
- Experience building reusable AI frameworks and enterprise reference architectures.
- Exposure to enterprise AI governance and responsible AI practices.

📌 Artificial Intelligence Architect (Bengaluru)
🏢 Vaisesika Consulting
📍 Bengaluru