Engineering Manager

Description :

- Partner with clients and key stakeholders - engage in technical discussions, manage expectations, and ensure successful, on-time delivery of enterprise AI solutions.

- Define and drive the engineering strategy - establish best practices, coding standards, and processes across teams.

- Drive technical architecture and strategic decision-making, ensuring systems are scalable, secure, and future-proof.

- Collaborate closely with product managers, designers, and data scientists to align engineering execution with business

goals and customer needs.

- Ensure projects are delivered on time, within scope, and at high quality, proactively identifying risks and removing roadblocks.

- Oversee system scalability, performance, and security, with a focus on AI/ML-powered applications.

- Manage hiring, resource planning, performance reviews, and career development of engineers to build a high-performing team.

- Foster a culture of innovation, ownership, and continuous learning, encouraging experimentation with new technologies and AI capabilities.

- Track and report on engineering KPIs (velocity, quality, uptime, customer impact) to continuously improve team efficiency and delivery.

- Collaborate with leadership on budgets, capacity planning, and long-term scaling of the engineering function.

Qualifications & Requirements :

Must-Haves :

- 10-15 years of experience in software engineering, with 3+ years in a managerial role.

- Strong foundation in full-stack development, backend systems, and cloud-native architectures.

- Hands-on experience with cloud platforms (AWS, Azure, or GCP) and building/deploying cloud-native applications.

- Proven experience leading engineering teams in agile environments, driving predictable delivery.

- Expertise in scalable, distributed systems and system design.

- Experience working directly with enterprise clients - managing technical discussions, expectations, and delivery.

- Excellent communication, organizational, and leadership skills.

- Ability to balance technical depth with business priorities and make pragmatic trade-offs.

- Demonstrated ability to hire, grow, and scale engineering teams.

- Builders mindset - proactive, adaptable, and able to lead in fast-changing environments.

Nice-to-Haves :

- Familiarity with AI/ML concepts, APIs, and model deployment.

- Prior experience in a startup or high-growth environment.

- Exposure to DevOps, CI/CD, and containerization (Docker, Kubernetes).