This role requires deep expertise in SaaS architectures, AI/ML integration, and agile practices, along with strong people leadership and business alignment skills.

You will guide teams to deliver high-quality, AI-enabled software at speed while fostering a culture of ownership, experimentation, and continuous improvement.

Key Responsibilities :

Technical Leadership :

- Drive cloud-native SaaS architecture and distributed systems design.

- Champion CI/CD pipelines for safe, automated, and rapid delivery.

- Guide teams on AI/ML workflows : data pipelines ? model training ? deployment ? monitoring.

Agile & Lean Practices :

- Promote story slicing into small, testable increments to maximize flow.

- Scale agile practices across teams while balancing autonomy and alignment.

- Foster iterative delivery and tight feedback loops.

People & Talent Management :

- Coach engineers to own delivery, experiment, and continuously improve.

- Mentor technical leads in both software engineering and AI/ML best practices.

- Build a culture of safe, frequent deployments and responsible AI adoption.

Operational Excellence :

- Ensure release reliability through monitoring, observability, and automated rollback.

- Embed MLOps and continuous retraining for AI-powered SaaS.

- Define metrics for deployment frequency, lead time, change failure rate, and AI model performance.

Strategic Thinking & Business Alignment :

- Align engineering throughput with product roadmaps and business outcomes.

- Balance speed of delivery with long-term maintainability and compliance (esp.in AI systems).

- Drive innovation while managing technical debt responsibly.

Communication & Change Leadership :

- Translate complex engineering and AI concepts into business value for executives and customers.

- Lead cultural change toward always deployable software and responsible AI integration.

- Influence stakeholders with clarity on trade-offs (speed vs. reliability vs. cost).

Qualifications :

- Bachelors/Masters degree in Computer Science or related field.

- 10 to 15+ years in software engineering, with 5+ years in leadership roles.

- Proven track record of leading teams in SaaS, cloud-native, and AI/ML-powered products.

- Strong knowledge of CI/CD, distributed systems, MLOps, and agile scaling.

- Excellent people leadership, coaching, and communication skills.

- Ability to align engineering strategy with business goals.