Engineering Manager
JOB DESCRIPTION
JOB REQUIREMENT
WHAT'S ON OFFER
CONTACT
Job Summary
Company Type:
Product
Technical Skills:
Management, Java
Location:
Ho Chi Minh - Viet Nam
Working Policy:
Salary:
$ 5,000 - $ 6,000
Job ID:
J00823
Status:
Close
Related Job:
Consulting Sales Manager / Sales Executive
Ho Chi Minh - Viet Nam
Outsource
- Sale
Pipeline Management: Drive pipeline creation and conversion to consistently meet and exceed sales targets. Client Development: Expand Capgemini's presence within key banking divisions by building and nurturing strong client relationships. Executive Engagement: Establish trusted relationships with business and technology CXOs to influence strategic decisions. Proactive Sales: Lead proactive sales initiatives to achieve and surpass business objectives. Strategic Planning: Define and execute strategic plans for focus areas, ensuring alignment with overall account goals. Opportunity Intelligence: Build account intelligence to uncover, shape, and develop new opportunities. Collaboration: Partner with Capgemini service lines and external partners to deliver integrated, end-to-end solutions. Proposal Development: Create compelling proposals, pricing strategies, and points of view for both proactive opportunities and formal procurement processes. Global CoE Engagement: Collaborate with Global Centers of Excellence (Data, Cloud & Infra, Fraud, Risk & Compliance) to secure and deliver successful deals. P&L Ownership: Hold full profit and loss responsibility for assigned divisions, business areas, or portfolios.
Negotiation
View detailsHead of Human Resources
Ho Chi Minh - Viet Nam
Product
- HR
- Management
Workforce Strategy: Design and implement workforce strategies aligned with the product roadmap and business P&L priorities. Organizational Design: Lead initiatives to support scaling, restructuring, and portfolio expansion. Talent Planning: Drive long-term talent density and succession planning for critical roles. Capability Frameworks: Build capability models directly linked to business outcomes. Executive Partnership: Act as a strategic advisor to senior leadership on people-related decisions. Business Translation: Translate business strategy into talent and capability requirements. Data Insights: Provide workforce analytics to guide growth and investment decisions. Leadership Development: Strengthen leadership pipelines and organizational resilience. Hiring Standards: Elevate recruitment standards and evaluation logic to ensure long-term talent quality. High-Performance Culture: Establish a culture anchored in accountability and clarity. Leadership Programs: Build leadership development initiatives tied to strategic priorities. Performance Management: Align performance systems with measurable business impact. AI Integration: Embed AI-driven tools into recruitment, workforce planning, and performance management. Predictive Analytics: Develop predictive talent models to anticipate capability gaps. Automation: Leverage automation to improve efficiency and decision quality. AI Governance: Promote responsible AI practices in people-related processes. HR Dashboards: Build dashboards connecting people metrics to business KPIs, operationalizing AI at scale. Cultural Alignment: Strengthen organizational culture focused on innovation, speed, and ownership. Behavioral Reinforcement: Ensure hiring and leadership behaviors reflect cultural direction. Agility & Governance: Balance agility with governance in a dynamic digital environment.
Negotiation
View detailsPlatform Lead
Others - Singapore
Product
- Backend
- Devops
- Data Engineering
Develop and expand distributed systems to handle large volumes of sensory, telemetry, and control data across cloud and edge environments, facilitating real-time connections for fleets of robots. Create the API Platform with a focus on high reliability, exceptional developer experience, and robust multimodal AI capabilities accessible through user-friendly APIs and SDKs. Establish extensive training and inference platforms for foundation models used in robot autonomy, teleoperation, and developer integrations. Devise data ingestion and streaming pipelines for real-time connectivity of robot fleets to the cloud, covering various data inputs such as video, LiDAR, joint states, and audio. Oversee and advance a modern cloud native infrastructure stack employing Kubernetes, Docker, and infrastructure as code tools. Ensure platform reliability through telemetry, monitoring, alerting, autoscaling, failover, and disaster recovery measures. Make infrastructure decisions pertaining to distributed storage, consensus protocols, GPU orchestration, network reliability, and API security. Foster collaboration across ML, robotics, and product teams to facilitate hardware in the loop simulation, policy rollout, continuous learning, and CI/CD workflows. Implement secure APIs featuring fine-grained access control, usage metering, rate limiting, and billing integration to accommodate a growing user base.