Teams at Deeplight AI

Own project controls, portfolio governance, delivery health analysis, RAID tracking, executive dashboards, KPI reporting, stage-gate compliance, and audit-ready documentation across enterprise AI and data projects. The role also improves PMO standards, reporting workflows, and project management practices while collaborating with project managers, technical leads, and senior stakeholders.

Leads enterprise data architecture for fixed-scope AI consultancy projects. Designs and governs Databricks Lakehouse platforms across AWS and Azure, advises executive clients, manages architecture roadmaps and technical risk, mentors cross-functional engineering and data teams, and establishes secure, compliant data foundations. The role requires strong consulting, stakeholder management, cloud, distributed processing, MLOps, and regulated financial-services experience.

Design and build scalable AWS Lakehouse solutions using Databricks, Delta Lake, PySpark, Kafka, and SQL. Develop batch and real-time pipelines for complex financial data, optimize cloud performance and costs, and implement banking-grade security, governance, encryption, and compliance. Support machine learning and MLOps workflows through feature engineering, MLflow, Docker, EKS, and SageMaker. Automate infrastructure and delivery with Terraform and CI/CD while communicating technical solutions to stakeholders.