We are looking for an AI Architect with 8+ years of experience in AI/ML, Data Science, and MLOps to lead the design and delivery of enterprise-grade AI/GenAI platforms.

This role will own architecture for LLM-powered assistants, RAG systems, agentic workflows, model serving, evaluation pipelines, and decision-intelligence applications on modern cloud platforms.

Key Responsibilities :

- Architect end-to-end AI systems across data, models, retrieval, orchestration, serving, evaluation, and monitoring

- Design and productionize LLM/GenAI solutions including RAG, multi-agent systems, tool use, memory, and workflow orchestration

- Define architecture for model training/fine-tuning, inference, prompt/system design, guardrails, and AI safety

- Establish MLOps standards for CI/CD, experiment tracking, model/version management, observability, evaluation, and cost-performance optimization

- Lead integration of Databricks, vector search, document pipelines, APIs, orchestration frameworks, and evaluation frameworks

- Translate ambiguous business problems into scalable AI solutions and guide delivery from PoC to production

- Mentor teams across AI engineering, data science, and platform engineering

Required Skills :

- 8+ years in AI/ML architecture, data science, or MLOps

- Strong hands-on experience with LLMs, RAG, agents, prompt/system design, and AI evaluation

- Experience building production AI systems with model deployment, monitoring, guardrails, and observability

- Strong understanding of ML pipelines, feature/data workflows, vector retrieval, and inference architectures

- Ability to communicate complex AI systems clearly to technical and non-technical stakeholders

Preferred :

- Experience with Databricks, MLflow, Fivetran, Jira, vector databases, and AI governance

- Background in marketing analytics, decision intelligence, or value-at-stake use cases