Senior Full Stack Engineer

We are looking for an experienced Senior Full Stack Engineer to build and enhance Audience Builder and Customer Data Platform (CDP) capabilities. The ideal candidate will have strong hands-on experience with React, TypeScript, Python, AI/ML, recommender systems, entity resolution, graph modeling, and graph databases. The role involves developing scalable customer segmentation, audience creation, preview, and activation solutions.

Key Responsibilities

• Build React-based Audience Builder UI and customer activation workflows.
• Develop APIs and backend services for audience creation, preview, segmentation, and activation.
• Develop scalable applications using Python, Node.js, REST APIs, and SQL.
• Integrate applications with Databricks, Delta Lake, ClickHouse, Redis, Kafka, and Event Hubs.
• Build AI-assisted segmentation and customer preview experiences.
• Develop and enhance recommender system capabilities.
• Implement entity resolution / record linkage solutions.
• Design and develop graph models and graph database solutions.
• Apply ML experimentation and evaluation techniques using metrics such as NDCG, MAP, Precision, and Recall.
• Develop unit tests, debug issues, perform RCA, and ensure production-quality solutions.
• Participate in HLD, LLD, architecture, data modeling, and technical design activities.
• Conduct code reviews and follow engineering standards and best practices.
• Collaborate with Product Managers, Architects, Data Scientists, QA, and other engineering teams.

Required Qualifications

• 7+ years of software/full-stack engineering experience.
• FAANG / Product-based company experience – Mandatory.
• Strong hands-on Python development experience.
• Strong experience with React, TypeScript, and Next.js.
• Experience with Pandas and PySpark.
• Strong AI/ML experience.
• Expertise in recommender systems, including matrix factorization, deep learning, and ranking models.
• Hands-on experience with entity resolution / record linkage.
• Strong experience with graph modeling and graph databases – Mandatory.
• Strong understanding of ML lifecycle, experimentation, and model evaluation.
• Experience with SQL and REST APIs.
• Hands-on experience with Databricks / Delta Lake.
• Experience with Redis and Kafka/Event Hubs.
• Strong analytical and problem-solving skills.

Preferred Qualifications

• Experience with real-time ML systems.
• Experience working with TB/PB-scale datasets.
• Experience with customer data platforms, personalization, or audience activation.
• Experience with large-scale distributed systems.
• Experience with cloud-based data and ML platforms.
• Experience working in Agile/Scrum environments.
• Strong customer-facing and technical communication skills.

ABOUT BRICKRED SYSTEMS

BrickRed Systems is a global leader in next-generation technology consulting and workforce solutions, specializing in delivering high-quality talent across digital, engineering, marketing, analytics, finance, operations, and business transformation domains. With a strong emphasis on innovation, scalability, and client success, BrickRed Systems helps organizations solve complex business challenges by providing skilled professionals across strategy, technology, creative, and operational functions. BrickRed fosters a culture of continuous learning, collaboration, and excellence, enabling professionals to contribute to high-impact global initiatives while advancing their careers.