Total 227 Manager job vacancies

Job Summary

Reporting to senior leadership, we are seeking an experienced Software Development Manager (AI-focused) to lead our AI and software engineering teams in building, deploying, and scaling production-grade, machine learning-driven multimodal AI solutions. This role oversees the end-to-end acquisition, development, and delivery of AI-centric software systems across all organizational units, ensuring solutions are high-quality, scalable, secure, and aligned with our business innovation and AI product roadmap. You will lead technical strategy, drive engineering excellence, and manage cross-functional initiatives to deliver industry-leading AI products.

Key Responsibilities

1. Lead and manage the AI software development team on a daily basis, setting clear goals, priorities, and performance expectations.
2. Plan project timelines, allocate resources effectively, and ensure on-time, on-budget delivery of AI software solutions and product initiatives.
3. Participate in system architecture design and key technical decisions for AI/ML systems, multimodal model deployment, and distributed AI platforms.
4. Drive continuous process improvements, including scaling Agile/Scrum, DevOps, MLOps, and CI/CD practices across the engineering organization.
5. Collaborate closely with product, design, QA, data science, and research teams to align technical delivery with product and business objectives.
6. Monitor project progress, quality, and risks proactively, implementing corrective actions to mitigate issues and ensure delivery excellence.
7. Recruit, mentor, and develop high-performing team members, fostering career growth and technical excellence within the engineering organization.
8. Cultivate a high-performing, inclusive, and positive team culture that prioritizes innovation, quality, and continuous learning.
9. Oversee the acquisition and development of AI software systems across all organizational units, ensuring consistency with technical standards and security best practices.
10. Monitor the results, performance, and quality of all AI software solutions and projects implemented within the organization, driving data-driven improvements.
11. Oversee the end-to-end development of Proof-of-Concept (PoC) initiatives and AI solutions, validating technical feasibility and business value for production scaling.
12. Provide deep technical expertise on software and platform feature development for AI systems, ensuring that appropriate security, compliance, and risk factors are fully addressed in all development work.

Qualifications

1. Master’s degree or higher in Computer Science, Information Technology, Programming & Systems Analysis, Science (Computer Studies), or a related engineering/technology faculty.
2. Experience Requirement: Minimum 5+ years of hands-on software development experience, with at least 2+ years of formal team management experience leading software engineering teams.
3. Technical Proficiency: Strong proficiency in mainstream programming languages (e.g., Python, Java, Go, C++) and modern software development tools, cloud platforms (AWS/GCP/Azure), and distributed systems.
4. AI/ML Expertise: Demonstrated experience building, deploying, and scaling AI/ML systems, large language models (LLMs), or multimodal AI solutions in a production environment.
5. System Architecture Expertise: Strong system design and architecture capabilities, with a proven track record of designing scalable, secure, and resilient AI software platforms.
6. Agile & DevOps Mastery: Deep familiarity with Agile methodologies (Scrum/Kanban), DevOps, MLOps, and CI/CD practices for enterprise software development.
7. Cross-Functional Leadership: Excellent communication, stakeholder management, and cross-functional collaboration skills to align technical and business teams.
8. Analytical & Problem-Solving Skills: Strong analytical, problem-solving, and decision-making abilities to resolve complex technical and operational challenges.
9. Preferred Qualifications: Experience with large-scale distributed systems, AI model deployment, cloud-native architectures, or enterprise AI product development is highly preferred.

Key Competencies

• Leadership and high-performing team management
• Deep technical breadth and depth in AI software development
• Results-driven, delivery-focused mindset
• Exceptional communication, coordination, and stakeholder management skills
• Strategic thinking and ability to align technical work with business goals

Job Summary

We are seeking a highly technical Platform Engineering Manager to lead the design, development, and continuous evolution of enterprise-grade cloud infrastructure, developer platforms, and large-scale distributed systems. This role will translate advanced research and technical requirements into highly scalable, reliable, and secure engineering solutions, lead a high-performing platform team, and drive the long-term technical strategy of the company’s core technology platforms.

Key Responsibilities

1. Lead, manage, and grow the platform engineering team in building, operating, and scaling cloud infrastructure, developer platforms, and mission-critical core systems.
2. Research, design, develop, test, and maintain computer systems, network software, system utilities, and platform-level components.
3. Analyze business and technical requirements, then design and implement software solutions based on computer science, engineering, and mathematical analysis principles.
4. Improve, optimize, and upgrade existing platforms to enhance system performance, stability, security, reliability, and scalability.
5. Establish and oversee software testing, validation, and quality assurance processes to ensure robust and production-ready systems.
6. Own end-to-end platform architecture design, including cloud-native, microservices, containerization, and distributed systems.
7. Drive and enforce engineering best practices including DevOps, SRE, CI/CD, infrastructure as code (IaC), and automation.
8. Monitor system health, performance, and reliability; identify bottlenecks and provide technical solutions to ensure stable and efficient operations.

Qualifications

1. PhD degree in Computer Science, Software Engineering, Electrical Engineering, or a closely related field (required).
2. 8+ years of professional experience in platform engineering, software engineering, systems engineering, or infrastructure development;
3. 3+ years of formal people management or leadership experience in a technology team.
4. Strong foundation in computer science including data structures, algorithms, operating systems, computer networks, and distributed systems.
5. Proficiency in at least one core programming language (e.g., Go, C++, Java, Python).
6. Deep expertise in system architecture, high-concurrency, high-availability, and large-scale distributed systems.
7. Hands-on experience with major cloud platforms (AWS, Azure, GCP) or hybrid/private cloud infrastructure.
8. Strong system performance tuning, troubleshooting, and problem-solving capabilities.
9. Experience in hardware-software integration is a strong advantage.
10. Excellent communication, leadership, and cross-functional collaboration skills.