Lead AI Engineering

Engineering Manager

Ho Chi Minh - Viet Nam

Offshore

Take charge in guiding and mentoring Agile teams to uphold engineering standards, sprint backlogs and plans, engineers' responsibilities and performance management, code quality, adherence to development guardrails, and testing. Collaborate with various cross-functional teams, architects, and product managers to ensure the execution and delivery of engineering goals. Drive the technology roadmap and contribute to the overall architecture and key components design for the current and future framework. Serve as a mediator between speed and quality while coaching engineers to be T-shaped, versatile, and take responsibility outside their core discipline. Take ownership of addressing technical debt and staying updated with modern development technologies and methodologies. Be accountable for the entire life-cycle development process and the deliveries of a team. Encourage self-sufficiency and discipline within the product engineering team. Spearhead initiatives for implementing efficient development and delivery processes. Inspire the product team to strive for continuous delivery and innovation. Oversee the career path development for engineering team members, in collaboration with the HR department.

Negotiation

Engineering Manager (Data Platform)

Ho Chi Minh - Viet Nam

Offshore

• Data Engineering
• Management

Agile Team Leadership: Guide and coach Agile teams to uphold engineering standards, manage sprint backlogs, clarify responsibilities, ensure code quality, enforce development guardrails, and drive rigorous testing practices. Agile Data Delivery: Oversee Agile execution across data platforms, maintaining excellence in data quality, testing, code review practices, CI/CD pipelines, documentation, and operational readiness. Cross-Functional Collaboration: Partner with data architects, product managers, analytics teams, platform engineers, and governance stakeholders to deliver data capabilities aligned with business priorities. Roadmap Ownership: Lead the execution of the data engineering roadmap, balancing immediate delivery needs with long-term platform sustainability. Architecture & Design: Contribute to the design of data platform architecture across ingestion, transformation, storage, and consumption layers. Engineer Development: Coach engineers to become T-shaped professionals, capable of working across batch processing, streaming, analytics engineering, and platform operations. Technical Debt Remediation: Own and prioritize the resolution of technical and data debt, including legacy pipelines, performance bottlenecks, and data quality issues. Modern Practices: Stay current with evolving data engineering tools, methodologies, and patterns-particularly within the Databricks ecosystem. Lifecycle Accountability: Ensure end-to-end ownership of data solutions, from design and build through deployment, monitoring, and ongoing support. Team Empowerment: Foster self-sufficient, disciplined teams accountable for the reliability and resilience of data products. Process Excellence: Lead initiatives to enhance data delivery through automation, observability, and operational best practices. Continuous Improvement: Inspire teams to innovate, experiment, and embrace continuous delivery as part of their culture. Career Growth: Drive career development for data engineers, partnering with HR to manage performance and define growth pathways.

Negotiation

Featured Job

AI/ML Engineer

Ho Chi Minh - Viet Nam

Offshore

• Machine Learning
• AI
• Data Engineering

Develop and optimize ML pipelines for both real-time and batch inference, applying modern MLOps best practices. Collaborate cross-functionally with data engineers and software developers to seamlessly integrate models into our client's banking platform, ensuring reliability, monitoring, and version control. Research, prototype, and productionize models in critical domains such as credit scoring, fraud detection, transaction classification, personalization, and conversational AI. Implement robust evaluation frameworks, including A/B testing and drift detection, to maintain accuracy and stability over time. Contribute to internal libraries and frameworks that standardize ML workflows and accelerate development across teams. Explore emerging techniques in LLMs, Generative AI, and reinforcement learning, assessing their applicability to our client's ecosystem. Mentor junior engineers and partner closely with product and infrastructure teams to ensure models are production-ready and scalable globally.

Negotiation