Engineering Manager
Weekday AI Gurugram, Haryana, India
Technology, Information and Internet · 11-50 employees
About the role
Lead and mentor engineering teams while driving technical execution across multiple projects to ensure high-quality, scalable solutions. Collaborate with cross-functional stakeholders to define technical roadmaps and establish engineering best practices.
What they look for
Requirements
Requires 5-8 years of professional software engineering experience with a strong background in technical leadership and people management. Candidates should possess deep knowledge of system design, software development lifecycles, and modern engineering methodologies.
Benefits
Full description
This role is for one of Weekday’s clients Salary range: Rs 2500000 - Rs 4000000 (ie INR 25 - 40 LPA)
Min Experience: 5+ years Location: Gurugram, Haryana, India JobType: full-time
We are looking for an experienced and hands-on Engineering Manager with 5–8 years of experience to lead engineering teams, drive technical execution, and contribute to the development of scalable, reliable, and high-quality technology solutions. The ideal candidate will combine strong engineering expertise with effective people management, while having a good understanding of Machine Learning concepts and their application in modern engineering environments.
As an Engineering Manager, you will work closely with product, design, data, and business teams to translate requirements into technical solutions, establish engineering best practices, and ensure projects are delivered efficiently. You will play a key role in mentoring engineers, improving development processes, and fostering a culture of ownership, collaboration, and continuous improvement.
Key Responsibilities• Lead, mentor, and manage a team of software engineers, supporting their technical and professional growth.
- Own engineering execution across multiple projects, ensuring timely delivery, quality, scalability, and reliability.
- Collaborate with Product Managers and cross-functional stakeholders to define technical roadmaps and priorities.
- Participate in system design, architecture discussions, code reviews, and technical decision-making.
- Establish engineering best practices around development, testing, deployment, monitoring, and documentation.
- Identify technical risks, performance bottlenecks, and opportunities for improving system reliability and scalability.
- Drive adoption of modern engineering tools, frameworks, and development methodologies.
- Build a strong culture of accountability, innovation, knowledge sharing, and continuous improvement.
- Track engineering metrics and proactively address delivery, quality, and productivity challenges.
- Support hiring, onboarding, performance management, and career development for engineering team members.
- Work with data and ML teams where required to integrate Machine Learning models and capabilities into production systems.
- Ensure ML-enabled products are developed with appropriate considerations for scalability, performance, monitoring, and maintainability.
Required Skills & Qualifications• 5–8 years of professional experience in software engineering, with relevant experience in technical leadership or people management.
- Strong understanding of software development lifecycle, system design, architecture, and engineering best practices.
- Experience managing, mentoring, and developing engineering teams.
- Strong problem-solving and analytical abilities.
- Excellent communication and stakeholder-management skills.
- Experience working with cloud platforms, APIs, databases, distributed systems, or modern software architectures.
- Ability to balance technical decisions, business priorities, and team development.
- Strong understanding of Agile/Scrum methodologies and modern engineering practices.
Good-to-Have Skills• Machine Learning concepts, workflows, and production use cases.
- Experience working with ML/AI engineers or data science teams.
- Familiarity with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Understanding of model deployment, ML pipelines, MLOps, or model monitoring.
- Exposure to Generative AI, LLMs, recommendation systems, predictive analytics, or other ML-driven applications.
- Experience building or managing highly scalable, data-intensive platforms.
What We Offer• Opportunity to lead and grow a high-performing engineering team.
- Exposure to challenging technical and business problems.
- A collaborative environment that encourages innovation and ownership.
- Opportunities to work with emerging technologies, including Machine Learning and AI.
- Strong career growth and leadership opportunities.
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