AI Architect

We turn customer challenges into growth opportunities.

Material is a global strategy partner to the world’s most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences.

We use deep human insights, design innovation and data to create experiences powered by modern technology. Our approaches speed engagement and growth for the companies we work with and transform relationships between businesses and the people they serve.

Srijan, a Material company, is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners. Be a part of an Awesome Tribe

Job Description:-

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

• 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

• Experience with Databricks, MLflow, Fivetran, Jira, vector databases, and AI governan
• Background in marketing analytics, decision intelligence, or value-at-stake use cases