• Develop and maintain distributed, high-availability applications using FastAPI, Flask, Uvicorn, TensorFlow, PyTorch, and OpenCV, connected to a vector database (PostgreSQL), in Cloud Native, containerized Docker environments • Manage code versioning with feature branches using Git Flow, promote branches to QA environments via Azure pipelines, and create branches for production release change management (GMUD) • Expose backend application routes in API Management (APIM)

• Support and continue the development of existing applications • Develop and maintain backend APIs and services • Work with modern frontend interfaces • Assist in incident resolution and bug fixes • Collaborate with the technical team to ensure operational continuity during the engagement

• Design and implement data validation pipelines and model evaluation workflows in a cloud environment (AWS) • Integrate data and metrics into automated, auditable, and scalable workflows • Modularize pipelines to enable reuse, testability, and maintainability • Work in partnership with Data Science, Data Engineering, and Product teams • Ensure best practices for versioning, logging, monitoring, and automated testing • Monitor model performance (drift, cost, accuracy) • Propose continuous improvements to data architecture and validation processes

• Lead innovative data solutions, drive strategic data initiatives, and mentor teams in technical excellence, ensuring the development and execution of scalable, high-impact data engineering projects that align with organizational goals. • Reports to Delivery Lead Partners with technology leaders and oversees the development of data strategy with architecture, data governance, security, data science, and compliance; creates reliable and repeatable large-scale data processes and automation. • Supports and enables multi-program engineering teams by applying deep technology centered consultative skills. • Provides expertise and comprehensive data engineering knowledge on current and future applications/systems and underlying information technology (IT) architecture. • Combines state of the art, creative and research based practices to drive higher levels of data excellence and serves as a technical point of contact for strategic projects. • Provides scalable data solutions to meet business needs that are consistent with enterprise standards, architectures and strategies by providing scientific, technical leadership and mentor-ship to other technical professionals to support enterprise needs and grow technical capabilities.