AVP - ENGINEERING

Mumbai, IndiaFull-timePosted Aug 7, 2026

๐—ง๐—ต๐—ถ๐˜€ ๐—ฟ๐—ผ๐—น๐—ฒ ๐—ถ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ผ๐—ป๐—ฒ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ช๐—ฒ๐—ฒ๐—ธ๐—ฑ๐—ฎ๐˜†'๐˜€ ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜๐˜€

๐—ฆ๐—ฎ๐—น๐—ฎ๐—ฟ๐˜† ๐—ฟ๐—ฎ๐—ป๐—ด๐—ฒ: ๐—ฅ๐˜€ ๐Ÿฒ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ - ๐—ฅ๐˜€ ๐Ÿณ๐Ÿฑ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ (๐—ถ๐—ฒ ๐—œ๐—ก๐—ฅ ๐Ÿฒ๐Ÿฌ-๐Ÿณ๐Ÿฑ ๐—Ÿ๐—ฃ๐—”)

Experience: 9+ yrs

Location: Mumbai, Maharashtra, India, anywhere, India

Job Type: Full-time

We are seeking an accomplishedย Associate Vice President (AVP) โ€“ Engineeringย to lead enterprise engineering delivery, release management, and production support operations across large-scale technology platforms. This role is ideal for experienced engineering leaders with strong expertise inย Java, Microservices Architecture, Cloud Technologies, DevOps, and Engineering Operationsย who are passionate about building high-performing teams and delivering reliable, scalable software solutions.

As an AVP โ€“ Engineering, you will provide strategic leadership across engineering, release management, and client support functions while driving operational excellence and engineering best practices. Working closely with product, architecture, DevOps, and executive stakeholders, you will ensure high-quality software delivery, strengthen engineering capabilities, and continuously improve release governance and customer support operations.

Requirements

Key Responsibilities

  • Lead, mentor, and scale engineering managers, technical leads, and backend engineering teams.
  • Drive architecture and technical direction for Java-based microservices applications and distributed enterprise platforms.
  • Establish engineering standards covering code quality, testing, API governance, CI/CD, security, and software development best practices.
  • Oversee end-to-end engineering delivery to ensure projects are completed on time, within scope, and to the highest quality standards.
  • Manage hiring, performance management, leadership development, and succession planning across engineering teams.
  • Build a culture of ownership, innovation, collaboration, and continuous improvement.
  • Monitor engineering KPIs including deployment frequency, sprint velocity, defect trends, and delivery performance.
  • Own the complete release management lifecycle, including planning, governance, deployment readiness, risk management, and post-release reviews.
  • Improve CI/CD pipelines, release automation, rollback strategies, and deployment reliability.
  • Lead production support operations by overseeing incident management, SLA compliance, root cause analysis (RCA), and preventive improvements.
  • Collaborate with cross-functional teams, customers, and executive stakeholders to resolve critical production issues and improve operational performance.
  • Drive process optimization, engineering governance, and technology modernization initiatives across the organization.

What Makes You a Great Fit

  • 9+ years of experience in software engineering with significant experience leading enterprise engineering teams.
  • Strong hands-on expertise inย Java,ย Spring Boot,ย Spring Cloud, and enterprise application development.
  • Deep understanding ofย Microservices Architecture, REST APIs, distributed systems, and event-driven application design.
  • Proven experience leading engineering delivery, release management, and production support in enterprise or SaaS environments.
  • Strong knowledge ofย AWS,ย Azure, orย Google Cloud Platform (GCP)ย along withย Docker,ย Kubernetes, and modern DevOps practices.
  • Experience implementing CI/CD pipelines, release governance, incident management, and operational excellence initiatives.
  • Excellent leadership, stakeholder management, communication, and people development skills.
  • Strong analytical and strategic thinking abilities with experience managing large, multi-layered engineering organizations.
  • Familiarity with Agile methodologies, Jira, Confluence, ITIL practices, and engineering governance frameworks.
  • Exposure toย Large Language Models (LLMs),ย Agentic AI, or AI-driven engineering practices is considered an added advantage.

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