AI Architect - LLM/RAG Solutions

We are looking for an experienced AI Architect to design and deliver scalable, secure, and enterprise-grade AI solutions aligned with business requirements.

The role will focus on AI/ML architecture, Generative AI, LLMs, RAG, cloud-native applications, and end-to-end solution delivery, while ensuring security, privacy, responsible AI, and operational readiness.

Key Responsibilities :

• Design and define end-to-end AI/ML solutions and architectures aligned with business and technology requirements.

• Define scalable AI solution architectures, integration patterns, and cloud-native application designs.

• Design and guide implementation of Generative AI, LLM, and RAG-based solutions for enterprise use cases.

• Translate business requirements into technical solutions considering performance, scalability, reliability, cost, security, and maintainability.

• Define technology choices, architecture standards, and best practices across the AI/ML lifecycle.

• Work closely with Data Science, Data Engineering, Software Engineering, Cloud, Security, and Product teams to deliver AI solutions.

• Provide technical leadership across PoCs, solution development, deployment, and productionisation of AI applications.

• Ensure AI solutions meet responsible AI, data privacy, security, governance, and compliance requirements.

• Evaluate emerging AI technologies, frameworks, and platforms and recommend their applicability to enterprise use cases.

• Support technical discussions, architecture reviews, stakeholder presentations, and solution demonstrations.

• Ensure solutions are designed for effective monitoring, operational support, and continuous improvement.

Required Skills & Experience :

• 8 - 11 years of overall experience in AI/ML, software engineering, data science, or related technology roles.

• Strong experience in AI/ML solution architecture and enterprise application development.

• Strong hands-on experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).

• Experience designing and implementing enterprise-grade AI solutions and AI/ML lifecycle processes.

• Strong understanding of LLM architectures, prompt engineering, embeddings, vector databases, RAG pipelines, and AI application patterns.

• Experience with Python and modern AI/ML frameworks.

• Good understanding of cloud-native AI solutions and major cloud platforms such as AWS, Azure, or GCP.

• Experience translating business requirements into scalable and secure technical architectures.

• Strong understanding of AI security, privacy, governance, responsible AI, and production readiness.

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

• Experience working in Agile delivery environments.

Good to Have :

• Experience with AI agents/agentic AI architectures.

• Experience with cloud AI platforms and managed LLM services.

• Knowledge of MLOps/LLMOps, model deployment, monitoring, and evaluation.

• Experience integrating AI solutions with enterprise applications, APIs, and data platforms.

• Relevant AI/ML or cloud certifications