Role overview:

The Director of Engineering & AI-Enabled Delivery will lead a multidisciplinary, remote organization of ~150 professionals across software engineering, business analysis, design, content, and internal platforms.

This leader will stabilize delivery, modernize engineering practices on cloud platforms, and build an AI-ready organization where teams use advanced tools responsibly and effectively to ship scalable products and services.

Key responsibilities:

Organization and leadership:

• Own the India-based engineering and delivery organization across SaaS products, custom development, and internal tools.
• Design and implement a clear team structure (managers, tech leads, product/BA leads) with defined charters and accountability.
• Build and develop high-performing managers and technical leaders; establish succession plans for key roles.

Engineering and AI-enabled delivery:

• Define and enforce a standardized SDLC and delivery model for all teams, including cross-functional ceremonies and quality gates.
• Establish cloud-native standards, reference architectures, and CI/CD pipelines for SaaS, web products, and internal tools.
• Integrate AI tools into the development lifecycle (coding copilots, test generation, documentation assistants) with clear guardrails and human accountability.

Quality, reliability, and operations:

• Set engineering standards for code quality, test automation, observability, and incident management.
• Oversee architecture and design reviews for major initiatives; challenge and coach teams on scalability, security, and maintainability.
• Own reliability metrics and continuous-improvement programs to reduce defects and incidents.

Talent development and culture:

• Create and maintain a comprehensive skill matrix covering technical, AI, cloud, and cross-functional skills across all roles.
• Define career paths and promotion criteria for engineers, managers, and cross-functional roles; make progression transparent and merit-based.
• Build a culture of technical excellence, accountability, and continuous learning, including mentoring programs and internal knowledge sharing.

Stakeholder and strategic alignment:

• Translate business goals into engineering roadmaps and capacity plans for SaaS products, client projects, and internal platforms.
• Partner with US-based leadership, product, and business stakeholders to prioritize initiatives and communicate outcomes clearly.
• Act as a visible champion for AI-enabled practices, helping non-technical leaders understand capabilities, risks, and ROI.

Experience and profile:

• 14–20 years in software engineering or platform engineering, including at least 5–7 years leading multi-team organizations.
• Proven track record running engineering for SaaS or product organizations plus custom implementation or services work.
• Strong hands-on background in modern architectures and cloud platforms (AWS, Azure, or GCP), including CI/CD and observability.
• Demonstrated experience integrating AI tools into software delivery and coaching teams on responsible, effective usage.
• Experience working with cross-functional teams (design, content, BAs) and aligning them around product outcomes.
• Confident communicator with global stakeholders; comfortable challenging existing practices and leading change.