Gen AI Architect

We are seeking an AI/Generative AI Architect who will be responsible for defining the end-to-end technical architecture for generative AI-powered data insight platforms. This role ensures that AI solutions are scalable, secure, cost-efficient, and aligned with business and regulatory requirements. We are building next-generation generative AI products that deliver actionable data insights at enterprise scale. Our platform combines Large Language Models (LLMs), advanced data engineering, knowledge graphs, and AI agents to help organizations analyze, understand, and act on their data faster and more intelligently. We focus on secure, scalable, explainable, and compliant AI systems designed for real-world enterprise use.

Responsibilities:

• Define and own the overall architecture for generative AI platforms, including LLMs, data layers, knowledge systems, and agent orchestration frameworks.
• Design scalable, cloud-native architectures that support high-performance AI workloads.
• Establish architectural patterns for retrieval-augmented generation (RAG), reasoning, evaluation, and observability.
• Ensure non-functional requirements such as reliability, security, compliance, latency, and cost efficiency are met.
• Provide technical leadership and guidance to engineering teams across AI, data, and platform domains.
• Design and maintain reference architectures for AI-driven data insight products.
• Collaborate with product managers to align architecture with business objectives.
• Partner with security and compliance teams to embed governance-by-design.
• Review designs and implementations to ensure architectural consistency and quality.
• Identify technical risks early and propose scalable, sustainable solutions.

Requirements:

• Master's degree or PhD in computer science, software engineering, or a related field.
• Minimum of 8-12 years of experience in software engineering, data platforms, and AI systems.
• Prior experience designing and delivering enterprise-scale AI or data products.
• Hands-on experience with cloud platforms and modern AI technologies is strongly preferred.
• Strong experience designing distributed, cloud-native systems.
• Deep understanding of generative AI, large language models, embeddings, and agent-based architectures.
• Experience with data platforms, APIs, and AI integration patterns.
• Knowledge of AI evaluation, monitoring, and observability frameworks.
• Familiarity with security, privacy, and governance considerations for AI systems.

Technical Skills Required:

• Distributed Systems Design.
• Search architecture (OpenSearch / Elasticsearch).
• API Design (REST / FastAPI).
• Cloud-native architecture (AWS / GCP / Azure).
• Kubernetes fundamentals.
• Data modeling at scale
• Multi-tenant SaaS design preferred.
• RAG architecture understanding preferred.
• Vector search familiarity preferred.
• Event-driven systems (Kafka / Pub/Sub) preferred.
• Security-aware design preferred.