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

Lead Engineering Manager