Solution Architect (Data + AI)

Engineering Manager (Data Platform)

Ho Chi Minh - Viet Nam

Offshore

• Data Engineering
• Management

This role focused on data engineering teams with data warehousing, streaming and batch patterns, CI/CD for data pipelines, Drive and coach Agile teams to deliver on engineering standards, sprint backlogs and plans, engineers' responsibilities and performance management, code quality, adherence to development guardrails, and testing; Drive Agile delivery across data platforms, ensuring high standards for; Data quality and testing, Code quality and review practices, CI/CD for data pipelines, Documentation and operational readiness Collaborate closely with data architects, product managers, analytics teams, platform teams, and governance stakeholders to deliver data capabilities aligned with business priorities Own the execution of the data engineering roadmap, balancing short-term delivery with long-term platform sustainability Contribute to data platform architecture and design, including ingestion, transformation, storage, and consumption layers Coach engineers to be T-shaped, capable of working across batch, streaming, analytics engineering, and platform concerns Own and prioritise the remediation of technical and data debt, including legacy pipelines, performance issues, and data quality gaps Stay current with modern data engineering tools, patterns, and methodologies, particularly within the Databricks ecosystem Be accountable for the full lifecycle of data solutions, from design through build, deployment, monitoring, and support Empower teams to be self-sufficient, disciplined, and accountable for the reliability of data products Lead initiatives to improve data delivery processes, including automation, observability, and operational excellence Motivate teams to continuously improve through innovation, experimentation, and continuous delivery Drive career development and progression for data engineers, partnering with HR on performance management and growth paths

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

Product Manager (Data & Models)

Ho Chi Minh - Viet Nam

Product

• Product Management
• AI

Designing data strategy and model integration for creating efficient data pipelines, evaluation frameworks, and annotation systems to maintain high-performance LLMs. Responsible for ensuring data quality standards and implementing bias mitigation and privacy-preserving techniques. Defining the product's core model roadmaps, taking into account technical feasibility, user needs, and ethical considerations. Collaboration with researchers to incorporate experimental breakthroughs into deployable features. Partnering with Engineering and Research teams to ensure model development aligns with product goals and advocating for transparency in model decision-making to build user trust. Analyzing usage patterns from open-source communities (Discord, Reddit, GitHub) to refine model behavior and address real-world edge cases, contributing to community-driven model evolution. Setting performance benchmarks, cost efficiency, and resource utilization standards for model scalability and reliability.

Negotiation