Automation Testing Principal/Lead
JOB DESCRIPTION
JOB REQUIREMENT
WHAT'S ON OFFER
CONTACT
Job Summary
Company Type:
Outsource
Technical Skills:
Automation Test, Management
Location:
Ho Chi Minh - Viet Nam
Working Policy:
Salary:
$ 2,300 - $ 3,000
Job ID:
J00186
Status:
Close
Related Job:
AI-Native Software Engineering Lead
Ho Chi Minh - Viet Nam
Outsource
- Backend
- AI
Responsible for developing and evolving the AI-native SDLC operating model, including agent workflow designs, verification gates, context management standards, and evaluation frameworks Build and lead multi-agent systems using orchestration layers such as Claude Code, GitHub Copilot Workspace, Cursor, LangGraph, CrewAI, or equivalent, from prototype to production Collaborate with the Director of Engineering to contribute to and maintain the company's AI toolchain selection criteria and evaluate tools with engineering rigor, providing internal guidance on when AI is beneficial and when it is not Establish engineering standards, agent evaluation loops, and AI output quality gates across the delivery organization Previous experience in a lead, principal, or staff engineer role with demonstrated cross-team influence Experience in outsourcing, consulting, or multi-client delivery environments Track record of building or leading an internal community of practice, guild, or AI adoption program Develop and continuously evolve the company's AI-native SDLC playbook, including standards, workflow templates, case studies, and guardrails that delivery teams can adopt immediately Design and lead internal upskilling programs that transition engineers from AI-assisted to AI-native working patterns Keep track of the AI capability frontier, model improvements, new agent frameworks, and emerging risks, translating signals into timely updates to KMS's practices Work closely alongside Delivery Teams as an AI transformation advisor and execution partner, identifying the highest-value automation opportunities across the SDLC and coordinating with the team to implement them Design and deploy agent-orchestrated workflows tailored to each client's stack, team maturity, and delivery context, with measurable ROI Build business cases for AI-native adoption with clients and account managers, framing the value in terms of velocity, quality, and cost Represent the company's AI-native engineering capabilities in client conversations, QBRs, and RFP responses as a credible technical authority
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.