Job Summary :

We are looking for a highly experienced AI Architect to define and lead the architecture of enterprise-scale AI solutions. The role will be responsible for translating business and technology requirements into scalable AI architectures, defining technical standards, and guiding engineering teams in building production-ready AI platforms and applications.

Key Responsibilities :

- Define end-to-end architecture for enterprise AI and machine learning solutions.

- Design scalable, secure, reliable, and production-ready AI platforms and applications.

- Define architecture patterns for Generative AI, LLM-based applications, RAG, AI agents, and intelligent automation.

- Evaluate and select appropriate AI models, frameworks, platforms, and technologies based on business and technical requirements.

- Design AI/ML pipelines covering data ingestion, preprocessing, model development, deployment, monitoring, and lifecycle management.

- Architect integration between AI solutions and enterprise applications, APIs, databases, and technology platforms.

- Define standards for model deployment, inference, scalability, performance, security, and observability.

- Work closely with engineering, data, product, security, and enterprise architecture teams.

- Provide technical leadership and architectural guidance to senior engineering teams.

- Evaluate emerging AI technologies and assess their applicability to enterprise use cases.

- Establish best practices around responsible AI, model governance, security, privacy, and compliance.

- Drive modernization of existing AI/ML platforms and applications.

- Review technical designs, architecture decisions, POCs, and implementation approaches.

- Identify technical risks and define mitigation strategies.

- Mentor senior engineers and architects and contribute to technology strategy and roadmaps.

Required Skills :

- 15 to 22 years of experience in software engineering, AI/ML, technology architecture, or related areas.

- Strong experience designing enterprise-scale AI/ML architectures.

- Expertise in Python and modern AI/ML frameworks.

- Strong understanding of Machine Learning, Deep Learning, NLP, and Generative AI.

- Hands-on experience with LLMs, RAG, embeddings, vector databases, prompt engineering, and AI agents.

- Strong understanding of APIs, microservices, distributed systems, and cloud-native architecture.

- Experience with ML lifecycle, MLOps, model deployment, monitoring, and governance.

- Strong understanding of cloud platforms and AI/ML infrastructure.

- Excellent architectural, technical leadership, problem-solving, and stakeholder-management skills.