Software Engineering Manager

Drive Capital; Gurugram District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Drive Capital seeks an experienced software development leader with a focus on AI/ML to manage engineering activities and deliver high-quality solutions. With at least 5 years of software development experience and 1 year in leadership, candidates should possess strong proficiency in Agile methodologies and a bachelor's degree in Engineering or Computer Science. The role involves overseeing the development lifecycle and collaborating with various stakeholders. Join a team aimed at creating robust AI solutions in Gurugram, India.

Qualifications

• Minimum of 5+ years of experience in software development.
• At least 1+ year in a software development leadership role.
• Proven experience managing or contributing to AI and Machine Learning products.

Responsibilities

• Manage engineering activities to deliver AI-driven solutions.
• Collaborate with stakeholders on project requirements.
• Lead the full development lifecycle for scalable AI/ML solutions.

Skills

Software development

AI/ML expertise

Agile methodologies

Problem-solving

Communication skills

Education

Bachelor’s degree in Engineering or Computer Science

Tools

TDD

CI/CD pipelines

Event-Driven Architecture

Service-Oriented Architecture

Job description

What You’ll Be Doing Every Day

• Meet business needs by managing engineering activities and consistently delivering high-quality solutions, with a focus on AI-driven features and systems.
• Collaborate with internal customers to gather business processes and project requirements, particularly related to data utilization and intelligent automation.
• Drive the full development lifecycle, including requirements analysis, feasibility estimates, architectural design, development, implementation, and operational support, ensuring scalable and robust AI/ML solutions.
• Work closely with Product Management partners on project planning, resource allocation, scheduling, and development timelines, especially for machine learning initiatives.
• Build and manage multi‑disciplinary software teams, overseeing development processes using industry best practices, including MLOps and model deployment standards.
• Lead design reviews, code reviews, and mentor engineers while promoting data‑informed decision‑making and ethical AI development.
• Partner with Talent Acquisition and hiring managers to recruit world‑class engineering talent, with a focus on AI/ML expertise.
• Manage multiple priorities in high‑pressure environments, identifying and resolving risks early to avoid cost and timeline overruns.
• Plan and participate in community meetups, fireside chats, information sessions, and technical and recruiting events.

What You Bring to the Table

• Minimum of 5+ years of experience in software development.
• At least 1+ year in a software development leadership role (Engineering Manager level or higher).
• Bachelor’s degree in Engineering, Computer Science, or equivalent professional experience.
• Proven experience managing or contributing to AI and Machine Learning products or features.
• Strong proficiency with Agile methodologies, development tools, and best practices.
• Hands‑on experience in environments using TDD and CI/CD pipelines.
• Solid knowledge of Object-Oriented Design, data structures, algorithm design, and complexity analysis.
• Experience defining and executing best practices across the full software development lifecycle.
• Proficiency in Event-Driven and Service-Oriented Architectures.
• Strong analytical and quantitative skills, with the ability to use data and metrics to drive decisions.
• Excellent problem‑solving abilities, attention to detail, and ability to multitask in deadline‑driven environments.
• Strong verbal and written communication skills with experience influencing peers and executives.
• Ability to understand technical concepts, evaluate trade-offs, and assess new ideas with internal and external partners.
• Proven collaboration with business, legal, engineering, design, and cross‑functional stakeholders.
• Strong sense of ownership, urgency, and accountability.
• Demonstrated leadership, mentoring, and people management skills.
• Track record of data‑driven decision‑making.

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