Lead Engineering Manager

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