Dci Consultants Private Limited · MyCareersFuture · 1mo
Manager (Software Engineering & Delivery)
Singapore- Posted
- 2026-09-01 (1mo)
- Place
- Singapore
- Commitment
- Contract
- Salary
- SGD 8,000 – 12,000 / month
- Experience
- 15+ YOE
- Education
- Bachelor's
- Department
- Information Technology
- Source
- MyCareersFuture (the employer’s own listing)
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Skills in this posting
coach and mentor staffTender PlanningTechnical ProposalsSoftware Development LifecycleLead Multidisciplinary TeamsMachine LearningArtificial IntelligenceComputer VisionGenerative AIData AnalyticsData EngineeringCybersecurity
Role Overview
The Manager, Software Engineering & Delivery will lead the software engineering organisation supporting the Traffic Management Systems Division and drive the Division's software, data, AI and digital transformation agenda.
The role is responsible for building engineering capabilities, developing technology roadmaps, modernising software delivery practices, and leading the adoption of Artificial Intelligence across software engineering, system operations, and intelligent mobility solutions.
The successful candidate will lead multidisciplinary teams comprising software managers, architects, AI engineers, data scientists, technical leads, software developers, DevSecOps engineers, platform engineers and system support personnel.
The Manager will shape the Division's future technology direction and identify opportunities to leverage AI, automation, advanced analytics and emerging technologies to improve operational efficiency, enhance customer outcomes and create differentiated solutions for intelligent transportation systems.
Key Responsibilities
People and Organisation Leadership
• Lead, manage, and develop a high-performing software engineering organisation.
• Coach and mentor software managers, architects, technical leads, developers, DevOps engineers, and platform engineers.
• Manage performance, competency development, career progression, training, and succession planning.
• Identify capability gaps and implement appropriate recruitment and workforce-development plans.
Resource and Capacity Management
• Plan and manage software capacity and capabilities to support projects, solution development, presales, maintenance, and system enhancements.
• Forecast resource demand and allocate personnel across projects and business priorities.
• Monitor resource utilisation, capability gaps, team performance, and delivery commitments.
• Coordinate with offshore and external development resources, ensuring consistent engineering, cybersecurity, quality, and delivery practices.
Software Engineering and Delivery Governance
• Establish and maintain a structured software development lifecycle covering requirements, architecture, design, development, integration, testing, deployment, and maintenance.
• Define and implement engineering standards, technical reviews, documentation requirements, and quality gates.
• Establish modern DevSecOps practices and automated development, testing, security, and delivery pipelines.
• Ensure compliance with company policies, engineering governance, cybersecurity requirements, applicable standards, and industry best practices.
• Monitor software quality and delivery performance and drive corrective actions and continuous improvement.
Project and Technical Leadership
• Provide technical and delivery leadership to project software teams throughout the project lifecycle.
• Review software architectures, engineering plans, resource estimates, schedules, technical risks, and development approaches.
• Support system integration, testing, deployment, customer acceptance, maintenance, and enhancement activities.
• Promote knowledge sharing and reuse of common platforms, frameworks, tools, components, and lessons learned across projects.
Technology Strategy and Innovation
• Develop a software technology and engineering roadmap aligned with the Division’s business and solution strategy.
• Evaluate emerging technologies including Generative AI, autonomous agents, computer vision, digital twins, predictive analytics and edge AI.
• Establish reusable AI components, platforms and accelerators that can be deployed across multiple projects.
• Keep abreast of developments in software engineering, traffic management systems, cloud and edge computing, cybersecurity, DevSecOps, data platforms, automation, and artificial intelligence.
• Evaluate and introduce suitable technologies, engineering practices, tools, and reusable software platforms.
• Promote responsible adoption of AI-assisted software engineering with appropriate security controls, technical reviews, and quality gates.
• Drive technology standardisation and reuse across projects to improve scalability and reduce development costs.
• Promote innovation culture and continuous experimentation within engineering teams.
Presales and Customer Engagement
• Support tenders and proposals through solution architecture, software estimates, resource plans, delivery strategies, risk assessments, and technical responses.
• Participate in customer meetings, technical workshops, solution presentations, system demonstrations, trade shows, and showcases.
• Present the Division’s software engineering capabilities, delivery practices, technology strengths, and quality controls.
• Ensure that software-related commitments are technically feasible, appropriately estimated, and deliverable.
Candidate Requirements
Qualifications and Experience
• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related discipline.
• 15 or more years of relevant experience, including at least 7 years in a senior software engineering, technology management, or delivery leadership role.
• Proven experience leading and developing multidisciplinary software teams.
• Proven experience leading AI, machine learning, data analytics or Generative AI initiatives within enterprise-scale environments.
• Demonstrated track record delivering AI-enabled products, platforms or operational solutions from concept to deployment.
• Experience defining AI strategies, business cases, governance frameworks and operating models.
• Experience managing multidisciplinary software, AI and data engineering teams.
• Strong experience managing the full software development lifecycle for complex, integrated, and mission-critical systems.
• Experience managing multiple projects, competing resource priorities, and geographically distributed or offshore teams.
• Experience establishing…
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