Lenovo

Service Delivery Director – Application Development (AI, Data, and Full Stack)

The Service Delivery Director will lead and manage the delivery of application development services, with a focus on AI-driven solutions, data platforms, and full-stack development. This role is responsible for ensuring the successful design, development, deployment, and maintenance of applications that align with business goals. The ideal candidate will have a strong background in AI, data engineering, and full-stack development, along with proven experience in managing large-scale IT service delivery teams.

Key Responsibilities:

1. Strategic Leadership:

   - Define and execute the strategic roadmap for application development, focusing on AI, data, and full-stack solutions.

   - Align service delivery objectives with business goals and ensure the delivery of high-quality, scalable, and innovative solutions.

   - Drive the adoption of AI and data-driven technologies to enhance business processes and customer experiences.

2. Service Delivery Management:

   - Oversee the end-to-end delivery of application development projects, ensuring timely and within-budget delivery.

   - Manage the development, deployment, and maintenance of AI models, data platforms, and full-stack applications.

   - Ensure adherence to best practices in software development, data engineering, and AI/ML model deployment.

3. Team Management:

   - Lead and mentor cross-functional teams, including developers, data scientists, AI engineers, and DevOps professionals.

   - Foster a culture of innovation, collaboration, and continuous improvement within the team.

   - Ensure teams are equipped with the necessary tools, training, and resources to deliver high-quality solutions.

4. Stakeholder Engagement:

   - Collaborate with internal stakeholders (e.g., business units, product managers) and external partners to understand requirements and deliver solutions.

   - Act as the primary point of contact for service delivery issues, ensuring effective communication and resolution.

   - Provide regular updates to senior leadership on project status, risks, and opportunities.

5. Technical Oversight:

   - Ensure the development and maintenance of robust, scalable, and secure applications.

   - Oversee the integration of AI/ML models into applications and data pipelines.

   - Monitor the performance of applications and data platforms, ensuring optimal functionality and user experience.

6. Quality Assurance and Compliance:

   - Implement and enforce quality assurance processes to ensure the reliability and performance of applications.

   - Ensure compliance with industry standards, data privacy regulations, and security protocols.

7. Innovation and Continuous Improvement:

   - Stay updated on emerging technologies and trends in AI, data engineering, and full-stack development.

   - Identify opportunities to leverage new technologies to improve service delivery and business outcomes.

   - Drive continuous improvement initiatives to enhance development processes and service quality.

Qualifications:

Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field.

- Experience:

  - 10+ years of experience in application development, with a focus on AI, data, and full-stack solutions.

  - 5+ years of experience in a leadership or managerial role, overseeing large-scale IT service delivery teams.

  - Proven track record of delivering complex, AI-driven applications and data platforms.

Technical Skills:

  - Strong knowledge of AI/ML frameworks and data engineering tools (e.g., Hadoop, Spark).

  - Expertise in full-stack development technologies (e.g., JavaScript, React, Node.js, Python, Java).

  - Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and DevOps practices.

  - Familiarity with data governance, security, and compliance standards.

Soft Skills:

  - Excellent leadership, communication, and stakeholder management skills.

  - Strong problem-solving and decision-making abilities.

  - Ability to manage multiple priorities in a fast-paced environment.

Preferred Qualifications

- Certifications in AI/ML, cloud platforms, or project management (e.g., PMP, Scrum Master).

- Experience in industries such as finance, healthcare, or e-commerce, where AI and data-driven solutions are critical.

- Knowledge of Agile and DevOps methodologies.

Key Performance Indicators (KPIs):

- On-time and within-budget delivery of application development projects.

- High user satisfaction and adoption rates for delivered solutions.

- Improved efficiency and performance of AI models and data platforms.

- Reduction in application downtime and maintenance issues.

- Successful implementation of innovation initiatives.