Technical Manager

Team Manager

Ha Noi - Viet Nam

Outsource

Own the overall performance and operations of the pre-sales function, managing multiple language-based teams (currently English- and Mandarin-speaking) through their Team Leaders. Coach and develop Team Leaders, ensuring consistent people management, performance standards, and team engagement across markets and languages. Act as the primary operational point of contact for the client stakeholder, aligning pre-sales execution with client expectations, product updates, and commercial goals. Drive pre-sales strategy, process optimization, and service quality to deliver strong customer experience and sales conversion for client products. Collaborate cross-functionally with internal Technical teams and other departments to ensure effective operations and smooth inquiry-to-sale conversion. Lead performance management through data analysis, reporting, and continuous improvement initiatives, sharing insights regularly with internal leadership and the client. Build and sustain a high-performance, resilient team culture in a fast-paced, scaling environment.

Negotiation

AI Automation Developer

Ho Chi Minh - Viet Nam

Product, Outsource

• AI
• Azure
• NodeJS
• ReactJS
• Typescript
• Devops

Create and implement GenAI-based applications across the client's operational processes Convert business needs into technical prototypes and operational applications Develop chat agents, copilots, and workflow automatons to enhance operational teams Leverage Microsoft Copilot Studio, Azure AI Services, and automation tools like Power Automate to craft scalable AI solutions Integrate GenAI features into existing systems and procedures Ensure responsible AI use, data accuracy, and compliance with internal security standards Keep abreast of new GenAI technologies, tools, and platforms through constant research and assessment Work collaboratively with various experts within operations, IT, and business units to document solutions and share knowledge across teams

Negotiation

AI Agent Ops Engineer

Ho Chi Minh - Viet Nam

Product

• AI
• Backend

Responsible for the design, construction, and upkeep of production-grade AI agent systems, including areas such as context engineering, instruction architecture, secure execution boundaries, tool integrations, multi-step orchestration, memory strategies, and reliability patterns. Manage the complete lifecycle of agents from prototyping to deployment, monitoring, and iterating. Develop and maintain an evaluation pipeline to measure agent quality, identify regressions, and enforce deployment gates through the use of golden datasets, scenario suites, and automated checks. Instrument agents and agent platforms for production observability, such as structured logging, tracing, metrics, latency monitoring, cost monitoring, and analysis of tool-call success rates and failures. Establish operational readiness standards, including rollback criteria, incident response playbooks, and recovery paths for common failure modes. Collaborate with product engineering teams to identify high-value use cases suitable for agent automation, operating in a Central Agent Ops role to enable AI product builders through AI enablers. Translate business workflows into tasks executable by agents and provide coaching to engineers on context engineering best practices, harness design, regression testing patterns, agent skill design, and tool-contract discipline. Streamline the onboarding process for teams adopting AI capabilities and train product engineers to independently extend and maintain agent skills. Develop and maintain organizational standards for agents, including naming conventions, context file structures, skill interface contracts, evaluation criteria, and release quality benchmarks. Establish and enforce "repo-as-discipline" practices to ensure that agent knowledge is versioned, reviewable, discoverable, and reusable. Cultivate a shared agent skills library for teams to reuse and extend, while keeping track of AI tooling/framework updates and external best practices to provide centralized information to product teams. Facilitate internal knowledge-sharing sessions, showcases, and retrospectives to efficiently propagate learnings.

Negotiation