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Wolters Kluwer

Manager Product Software Engineering

Posted Yesterday
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In-Office
Pune, Maharashtra, IND
Senior level
In-Office
Pune, Maharashtra, IND
Senior level
The Senior Manager of Software Engineering leads product engineering teams, drives technical excellence, oversees project execution, and promotes innovative practices using AI tools while collaborating across various functions and stakeholders.
The summary above was generated by AI

Job Title: Senior Manager – Software Engineering

Role Summary

The Senior Manager, Software Engineering is responsible for leading and scaling high‑performing product engineering teams while driving technical excellence, timely delivery, and strategic innovation. This role requires strong people leadership, deep technical expertise, cross‑functional collaboration, and the ability to leverage modern engineering practices including AI‑assisted development tools to accelerate delivery and improve quality.

You will partner closely with Product Management, UX, QA, DevOps, and business stakeholders to define and execute product roadmaps, contribute to long‑term technical strategy, and foster a culture of ownership, accountability, and continuous learning.

Key Responsibilities

Engineering Leadership & People Management

  • Lead and manage a sizable, distributed team of software engineers, fostering a positive, inclusive, and high‑performing culture.
  • Provide strong technical and managerial leadership, offering guidance on complex engineering challenges and critical decision‑making.
  • Mentor, coach, and develop engineering managers and individual contributors, supporting career growth and succession planning.
  • Conduct regular performance evaluations, provide actionable feedback, and identify development opportunities.
  • Build trust within teams by setting clear expectations, ensuring accountability, and promoting transparency.

Delivery & Execution Excellence

  • Plan, prioritize, and schedule work to ensure efficient resource utilization and predictable delivery.
  • Ensure timely delivery of projects while balancing scope, quality, risk, and resources.
  • Monitor development processes, framework adoption, and project progress to ensure adherence to engineering standards and best practices.
  • Estimate project cost, effort, and resource needs; allocate resources effectively across initiatives.
  • Continuously monitor ongoing processes and outcomes, providing feedback and driving improvements.

Technical & Architectural Leadership

  • Drive engineering best practices across code quality, testing strategies, CI/CD pipelines, and Agile methodologies.
  • Contribute to architectural decisions and long‑term technical strategy aligned with business goals.
  • Ensure strong understanding and application of modern software architecture, cloud technologies, and scalable system design.
  • Provide oversight and guidance on DevOps practices, microservices architecture, and platform engineering.
  • Promote automation across development, testing, deployment, and operational workflows.

AI Tools & Modern Engineering Practices

  • Drive adoption of AI‑assisted development tools (e.g., code generation, code review assistance, test automation, DevOps intelligence).
  • Leverage AI tools to improve developer productivity, reduce cycle time, enhance code quality, and accelerate troubleshooting.
  • Encourage responsible and secure usage of AI tools in engineering workflows, following organizational and compliance guidelines.
  • Use data and AI‑driven insights to improve delivery predictability, quality metrics, and engineering efficiency.
  • Stay informed on emerging AI trends and assess their applicability to product engineering and platform evolution.

Stakeholder & Cross‑Functional Collaboration

  • Communicate effectively in a matrixed organization with senior leadership, stakeholders, and cross‑functional partners.
  • Collaborate closely with Product Management, UX, QA, DevOps, and business stakeholders to define, prioritize, and execute product roadmaps.
  • Partner across teams, geographies, and functions to enable smooth integrations and successful product launches.
  • Influence without authority and resolve dependencies across teams to ensure alignment and progress.

Required Skills & Expertise

Core Technical & Engineering Skills

  • Product Software Engineering: Strong expertise in designing, developing, testing, and delivering scalable software products.
  • Cloud Computing: Hands‑on understanding of cloud platforms (AWS, Azure, GCP), cloud‑native architectures, and managed services.
  • DevOps: Experience with automation, CI/CD, continuous delivery, monitoring, and rapid feedback loops.
  • Software Architecture: Strong understanding of microservices, APIs, distributed systems, and platform engineering.
  • APIs & Integrations: Experience designing, securing, documenting, and managing APIs.
  • Automation: Expertise in designing and optimizing automated systems across SDLC.
  • Frameworks: Strong knowledge of modern development frameworks and best practices.

Ways of Working

  • Agile Methodologies: Experience leading teams using Agile/Scrum/Kanban with a strong focus on continuous improvement.
  • Implementation & Delivery: Proven ability to execute plans effectively and deliver complex initiatives.
  • Problem Solving & Analysis: Ability to break down complex problems and develop practical, scalable solutions.
  • Spec Driven development
  • AI oriented SDLC

People & Leadership Skills

  • People Management: Strong skills in coaching, delegation, conflict resolution, motivation, and performance management.
  • Stakeholder Management: Excellent communication and collaboration skills across technical and non‑technical audiences.
  • Influence & Collaboration: Ability to lead through influence in a matrixed environment.

Competencies & Leadership Behaviours

  • Judgement & Decision Making
  • Accountability & Ownership
  • Inclusive Collaboration
  • Inspiration & Alignment
  • Courage to Take Smart Risks

Preferred Qualifications

  • Prior experience leading multi‑team or multi‑location engineering organizations.
  • Exposure to AI/ML‑powered engineering platforms or developer productivity tools.
  • Experience in large‑scale product organizations or SaaS platforms.
Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Top Skills

Agile Methodologies
Ai-Assisted Development Tools
APIs
Automation
Azure
Ci/Cd
Cloud Platforms (Aws
Gcp)
Microservices

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