Job description
This role is for one of the Weekday's clients Salary range: Rs 5000000 - Rs 12000000 (ie INR 50-120 LPA) Min Experience: 6 years Location: NCR JobType: full-time We are seeking a highly experienced Chief Architect to lead the end-to-end design and development of an advanced AI-powered traffic intelligence platform.
This is a hands-on leadership role focused on building a scalable, real-time, and enterprise-grade system that integrates data, machine learning, and geospatial intelligence.
You will define the technical vision, drive architectural decisions, and ensure the platform delivers high performance, reliability, and real-time insights for large-scale deployments.
Key Responsibilities Own and define the end-to-end system architecture, from data ingestion to real-time analytics and API delivery Design scalable data platforms using modern lakehouse architecture (Bronze/Silver/Gold layers) Architect real-time data pipelines using streaming technologies to handle high-volume, low-latency workloads Develop and implement data fusion and conflation strategies for integrating multiple geospatial and telemetry data sources Lead the design and deployment of machine learning models for traffic prediction, ETA, anomaly detection, and forecasting Build and scale MLOps infrastructure including feature stores, model deployment, monitoring, and retraining pipelines Make critical build vs.
buy decisions across infrastructure, tools, and platforms Define multi-tenancy, security, and governance frameworks for enterprise and public-sector usage Establish engineering best practices across code quality, testing, CI/CD, and observability Collaborate with cross-functional teams including product, engineering, and stakeholders to align architecture with business goals Mentor senior engineers and guide technical decision-making across the organization Act as the technical representative in customer discussions, architecture reviews, and solution design sessions What Makes You a Great Fit Strong experience architecting real-time data systems using technologies like Kafka, Flink, or similar streaming frameworks Proven ability to design and deploy end-to-end machine learning systems at scale Deep understanding of MLOps tools and workflows (e.
g., model lifecycle management, feature stores, monitoring) Hands-on expertise in cloud data platforms and lakehouse architectures (Iceberg, Delta, or similar) Strong programming skills in Python and at least one JVM language (Java/Scala), along with advanced SQL proficiency Solid understanding of geospatial data concepts, map data processing, and spatial algorithms Experience working with large-scale distributed systems and multi-tenant architectures Ability to balance performance, scalability, cost, and governance in complex systems Strong problem-solving skills with a hands-on approach to complex technical challenges Excellent communication skills with the ability to explain complex systems to both technical and non-technical stakeholders Demonstrated ownership mindset with the ability to define and drive long-term technical vision
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