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Senior Engineering Manager

salary Salary :

₹55 - 75 yearly

icon building Company : Weekday Ai
icon briefcase Job Type : Full Time

Number of Applicants

 : 

000+

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Job Description - Senior Engineering Manager

Description

This role is for one of the Weekday's clients

Salary range: Rs 5500000 - Rs 7500000 (ie INR 55 - 75 LPA)

Experience: 12+ yrs

Location: Chennai

Job Type: full-time

We are seeking an experienced Senior Engineering Manager to lead the engineering organization for a strategic AI-native SaaS product focused on transforming customer engagement, marketing automation, and data-driven business operations.

This role requires a strong combination of technical leadership, people management, and execution excellence. You will lead multiple engineering teams, drive product delivery, establish architectural standards, and collaborate closely with product, design, data science, and business stakeholders across global teams.

As a senior leader, you will be responsible for building high-performing engineering teams, scaling organizational processes, and delivering innovative AI-powered capabilities that create meaningful business impact.



Requirements

Key Responsibilities

Engineering Leadership & Team Management

  • Lead and manage a multidisciplinary engineering organization comprising backend engineers, frontend engineers, applied AI/ML engineers, QA engineers, and technical leads.
  • Build, mentor, and develop high-performing engineering teams while fostering a culture of ownership, accountability, and continuous learning.
  • Define career development frameworks, conduct performance reviews, and support succession planning.
  • Own hiring strategies and recruitment efforts to attract and retain top engineering talent.

Product Delivery & Execution

  • Own end-to-end engineering execution, including sprint planning, roadmap delivery, dependency management, and release governance.
  • Drive predictable and high-quality software delivery while maintaining engineering velocity.
  • Track risks, manage escalations, and provide clear progress updates to executive leadership.
  • Ensure alignment between engineering priorities and business objectives.

Technical Strategy & Architecture

  • Define and enforce engineering best practices, architectural principles, and development standards.
  • Lead architecture reviews and guide teams on scalable, maintainable, and resilient system design.
  • Establish standards for code quality, testing, observability, reliability, and security.
  • Drive adoption of modern architectural patterns including microservices, event-driven systems, and domain-driven design principles.

AI & Platform Innovation

  • Partner with AI/ML teams to develop and scale intelligent product capabilities.
  • Drive engineering decisions related to LLM integrations, agent-based systems, AI workflows, and data-driven automation.
  • Collaborate with technical architects and product leaders to define the long-term AI and platform roadmap.
  • Evaluate emerging technologies and identify opportunities for innovation.

Cross-Functional Collaboration

  • Serve as the primary engineering partner to Product Management, Design, Data Science, and Business stakeholders.
  • Translate business requirements into actionable engineering plans and technical solutions.
  • Facilitate effective communication across globally distributed teams and stakeholders.
  • Ensure successful coordination with platform, infrastructure, security, and shared services teams.

Engineering Excellence & Culture

  • Foster a high-trust environment that encourages innovation, ownership, and continuous improvement.
  • Promote engineering excellence through mentorship, design reviews, and technical guidance.
  • Champion operational excellence, system reliability, and customer-centric product development.
  • Drive initiatives that improve team productivity, developer experience, and organizational scalability.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 12+ years of software engineering experience with at least 5+ years in engineering leadership roles.
  • Proven experience leading and scaling teams of 15+ engineers, including technical leads and managers.
  • Strong technical expertise in Java-based backend systems and modern software architecture.
  • Deep understanding of distributed systems, microservices architecture, and event-driven platforms.
  • Experience building and operating large-scale SaaS applications in cloud environments.
  • Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
  • Strong knowledge of modern data technologies including relational and NoSQL databases, messaging systems, caching solutions, and search platforms.
  • Demonstrated success delivering complex products in fast-paced, high-growth environments.
  • Strong stakeholder management and cross-functional leadership skills.

Preferred Qualifications

  • Experience leading engineering teams building AI-native products and intelligent automation platforms.
  • Exposure to Large Language Models (LLMs), AI agents, orchestration frameworks, and machine learning applications.
  • Experience with workflow orchestration platforms and distributed task processing systems.
  • Background in marketing technology, customer engagement platforms, SaaS products, or enterprise software.
  • Experience managing both frontend and backend engineering teams.
  • Familiarity with modern observability, monitoring, and platform engineering practices.

Must-Have Skills

  • Artificial Intelligence
  • Java
  • Distributed Systems

Good-to-Have Skills

  • Agentic AI
  • Machine Learning Platforms
  • Microservices Architecture
  • Cloud Computing (AWS/Azure/GCP)
  • Event-Driven Architecture
  • SaaS Product Development
  • Engineering Leadership

What Success Looks Like

  • Consistently deliver high-quality product releases aligned with business goals.
  • Build and scale a world-class engineering organization.
  • Establish strong technical standards and engineering best practices.
  • Successfully deliver innovative AI-powered capabilities that create measurable customer value.
  • Foster a culture of accountability, collaboration, and engineering excellence.
  • Drive long-term platform scalability, reliability, and product innovation.
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