Data & AI Architect

Position: Data & AI Architect About the Role We are looking for a Data & AI Architect to lead the design and architecture of modern, scalable Data, AI, and GenAI solutions for enterprise clients. The role will focus on translating business requirements into robust technology architectures across Azure, Databricks, Lakehouse, AI/ML, and Generative AI. The architect will work closely with business stakeholders and cross-functional engineering teams to define solution architecture, drive PoCs and architecture workshops, and ensure solutions meet requirements for security, governance, scalability, performance, and cost optimization. Key Responsibilities • Design end-to-end data and AI architectures (data lakes, warehouses, lakehouses, MLOps pipelines, GenAI/LLM solutions) aligned with business goals • Lead technical discovery with stakeholders to define requirements, constraints, and success criteria • Evaluate and select tools, platforms, and Azure cloud services for data ingestion, storage, processing, and AI model deployment • Define data governance, security, and compliance standards (data privacy, access control, lineage, quality) • Architect scalable ML/AI pipelines — from data preparation and feature engineering to model training, deployment, and monitoring • Guide integration of GenAI/LLM capabilities (RAG, fine-tuning, agentic workflows) into enterprise systems • Produce architecture diagrams, technical documentation, and design decision records • Partner with data engineers, data scientists, and DevOps/MLOps teams to ensure solutions are production-ready • Conduct architecture reviews, performance tuning, and cost optimization • Stay current with emerging trends in data platforms, AI/ML, and cloud technologies; advise leadership on adoption • Mentor engineering teams on architectural best practices Required Qualifications • Bachelor's or Master's degree in Computer Science, Data Engineering, or related field (or equivalent experience) • 7+ years in data engineering/architecture roles, with 3+ years in a solution/enterprise architect capacity • Deep expertise in cloud data platforms • Strong understanding of data modeling, ETL/ELT pipelines, and distributed computing • Hands-on experience with ML/AI frameworks • Practical experience with LLM/GenAI architectures (vector databases, RAG, prompt engineering, agent frameworks) • Solid grasp of data governance, security, and regulatory compliance • Proficiency in SQL and Python; familiarity with infrastructure-as-code (Terraform, CloudFormation) • Excellent communication skills — able to translate technical concepts for non-technical stakeholders Preferred Qualifications • Cloud certifications (Azure Solutions Architect or Data/AI specialty) • Experience with enterprise architecture frameworks (TOGAF) • Background in a consulting or client-facing solution delivery role • Experience with real-time streaming architectures and data mesh principles What We Offer: At Delphi, we are dedicated to creating an environment where you can thrive, both professionally and personally. Our competitive compensation package, performance-based incentives, and health benefits are designed to ensure you're well-supported. We believe in your continuous growth and offer company- sponsored certifications, training programs, and skill-building opportunities to help you succeed. We foster a culture of inclusivity and support, with remote work options and a fully supported work-from- home setup to ensure your comfort and productivity. Our positive and inclusive culture includes team activities, wellness and mental health programs to ensure you feel supported.

Bachelor's or Master's degree in Computer Science, Data Engineering, or related field (or equivalent experience); 7+ years in data engineering/architecture roles, with 3+ years in a solution/enterprise architect capacity; Deep expertise in cloud data platforms; Strong understanding of data modeling, ETL/ELT pipelines, and distributed computing; Hands-on experience with ML/AI frameworks; Practical experience with LLM/GenAI architectures (vector databases, RAG, prompt engineering, agent frameworks); Solid grasp of data governance, security, and regulatory compliance; Proficiency in SQL and Python; familiarity with infrastructure-as-code (Terraform, CloudFormation); Excellent communication skills

Design end-to-end data and AI architectures (data lakes, warehouses, lakehouses, MLOps pipelines, GenAI/LLM solutions) aligned with business goals; Lead technical discovery with stakeholders to define requirements, constraints, and success criteria; Evaluate and select tools, platforms, and Azure cloud services for data ingestion, storage, processing, and AI model deployment; Define data governance, security, and compliance standards (data privacy, access control, lineage, quality); Architect scalable ML/AI pipelines — from data preparation and feature engineering to model training, deployment, and monitoring; Guide integration of GenAI/LLM capabilities (RAG, fine-tuning, agentic workflows) into enterprise systems; Produce architecture diagrams, technical documentation, and design decision records; Partner with data engineers, data scientists, and DevOps/MLOps teams to ensure solutions are production-ready; Conduct architecture reviews, performance tuning, and cost optimization; Stay current with emerging trends in data platforms, AI/ML, and cloud technologies; advise leadership on adoption; Mentor engineering teams on architectural best practices