Senior Delivery Manager - AI & Data Engineering

Job Description:

Senior Delivery Manager (AI & Data Engineering)

Experience: 12-20 Years

Location: Remote (Bengaluru)

Notice Period: Immediate to 30 Days Preferred

Key Responsibilities:1. Delivery Leadership:

• Lead multiple AI and Data Engineering delivery pods consisting of Scrum Leads, AI Engineers, Data Engineers, and Project Managers.

• Own end-to-end delivery execution across concurrent client engagements.

• Drive sprint planning, backlog prioritization, delivery velocity, and release management.

• Ensure projects are delivered on schedule, within scope, and with high quality.

• Monitor delivery risks, proactively identify blockers, and resolve issues before they impact clients.

• Establish delivery governance, operational discipline, and scalable execution processes in a dynamic startup environment.

• Ensure Statements of Work (SOWs) are executed accurately, meeting contractual commitments and client expectations.

• Track delivery metrics, quality standards, resource utilization, and overall project health.

2. Team Leadership & People Management:

• Lead, mentor, and develop AI Engineers, Data Engineers, Engineering Managers, Scrum Leads, and Project Managers.

• Build a culture of accountability, ownership, and continuous improvement.

• Define performance expectations, delivery standards, and escalation frameworks.

• Conduct performance reviews, coaching sessions, and career development planning.

• Identify skill gaps and establish learning and development initiatives.

• Foster cross-functional collaboration across engineering, product, and business teams.

• Support hiring by conducting technical interviews and evaluating both technical expertise and cultural alignment.

3. Client & Stakeholder Management:

• Serve as the primary delivery leader for enterprise client engagements.

• Participate in client discovery workshops, solution discussions, delivery reviews, and executive steering meetings.

• Communicate complex technical challenges in clear business terms for executive stakeholders.

• Manage delivery escalations professionally while maintaining strong client relationships.

• Ensure transparent communication through regular project updates, status reporting, and risk management.

• Represent the organization confidently in discussions with senior leadership and client executives.

4. Technical Leadership:

• Provide architectural guidance and technical governance across AI and Data Engineering initiatives.

• Review solution designs, validate implementation approaches, and ensure adherence to engineering best practices.

• Guide teams in building scalable, production-grade AI platforms and enterprise data solutions.

• Stay current with emerging AI technologies, frameworks, and enterprise architecture patterns.

• Collaborate with technical leadership on platform strategy, solution architecture, and technology roadmap.

• Review technical decisions, identify architectural risks, and proactively address technical debt.

5. Operational Excellence:

• Establish standardized delivery frameworks, playbooks, and governance processes.

• Drive sprint retrospectives, knowledge-sharing initiatives, and continuous process improvements.

• Monitor team capacity planning, resource allocation, and utilization across multiple delivery pods.

• Develop scalable operational practices supporting business growth and delivery excellence.

• Enable leadership through delivery dashboards, KPIs, forecasting, and performance reporting.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related discipline.

• 12-20 years of experience in software engineering, AI, data engineering, or enterprise technology delivery.

• Minimum 5 years of experience leading large technical delivery teams or engineering organizations.

• Proven success delivering enterprise AI, Machine Learning, Data Engineering, or Digital Transformation programs.

• Experience managing multiple concurrent client engagements in consulting, professional services, or product organizations.

• Experience working in startup or high-growth environments is highly preferred.

• Strong understanding of Agile, Scrum, Kanban, and enterprise delivery methodologies.

Required Technical Skills:

• AI & Machine Learning

• Data Engineering

• Cloud & DevOps

• Architecture & Engineering

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