Data Engineer

Lead Software Engineer (Distributed Computing)

Ho Chi Minh - Viet Nam

Product

Translate business objectives to technical solutions. Lead R&D to discover novel approaches and propose technical solutions. Lead the design and development of a next-generation AI-powered software transformation framework capable of accelerating the modernization of complex analytical applications. Own key architectural decisions for converting legacy computational tools into scalable cloud-native solutions. Define technical direction, engineering standards, and transformation methodologies for AI-assisted software modernization. Guide the use of AI agents, LLMs, and emerging AI engineering techniques to automate software analysis, code transformation, validation, and optimization. Lead technical investigations into how existing software systems can be restructured, decomposed, or re-implemented to operate efficiently in distributed environments. Collaborate with distributed computing specialists to design target architectures using Spark-based execution models for large-scale data processing. Build and guide the development of reusable transformation pipelines, automation tooling, and engineering frameworks that enable software modernization at scale. Establish validation strategies, quality frameworks, and technical review processes to ensure transformed systems maintain functional correctness and reproducibility. Drive architectural decisions around scalability, maintainability, performance, infrastructure efficiency, and long-term platform evolution. Mentor senior and mid-level engineers, review technical designs, and raise the engineering quality of the team. Partner with domain experts to understand application requirements and translate them into scalable, practical technical solutions. Prototype and evaluate new AI-assisted engineering approaches that improve transformation speed, engineering productivity, and software quality. Contribute to the organization's long-term strategy for AI-driven software modernization, distributed computing, and engineering automation.

Negotiation

Salesforce Engineer (IC2)

Ho Chi Minh - Viet Nam

Outsource

• Salesforce

#Salesforce Engineering (Quote-to-Cash) Build and maintain Salesforce processes from Quote through to Cash Work full-stack on the platform: declarative (data model, Flows, validation, security model) and programmatic (Apex, Lightning Web Components) Implement changes safely on a production system used by Go-to-Market every day#Integrations & System Interfaces Maintain and further develop the integrations between Salesforce and internal/external systems (customer portal, HubSpot, license management, billing/ERP, and others) Design and operate integrations using Salesforce REST/SOAP APIs and standard integration patterns Own the health of these interfaces: monitoring, error handling, and data consistency#Collaboration with Go-to-Market / RevOps Partner with RevOps and GTM to translate business needs into robust technical implementations Challenge requirements where they create risk or technical debt Coordinate handoffs at the Lead-to-Quote / Quote-to-Cash boundary#Reliability, Security & Change Safety Protect a revenue-critical system: change control, testing, backup/rollback awareness Apply JTL security and compliance standards to Salesforce work#Optional / stretch With spare capacity, support tech-heavy Lead-to-Quote topics in Salesforce (optional; primary ownership of Lead-to-Quote stays with RevOps)

Negotiation

Senior Bioinformatics Engineer

Ho Chi Minh - Viet Nam

Product

• Data Science

Act as the main expert on bioinformatics for engineering teams developing cloud-native bioinformatics software. Work with software architects to convert scientific workflows into scalable distributed computing architectures. Help engineers understand the computational characteristics, assumptions, and limitations of existing bioinformatics tools. Confirm that modernized applications maintain scientific correctness and produce reproducible results. Establish biological data models, metadata standards, controlled vocabularies, and best practices for data harmonization. Assist engineering teams in developing scalable approaches for processing large genomic and multi-omics datasets. Evaluate open-source bioinformatics software and identify opportunities for cloud-native modernization. Collaborate with distributed computing specialists to determine how algorithms can be parallelized using large-scale execution frameworks. Create validation datasets, benchmarking methodologies, and acceptance criteria for transformed applications. Review engineering designs to ensure biological accuracy and scientific integrity. Collaborate with AI engineering teams on using AI-assisted software transformation while ensuring scientific correctness. Stay up to date with advances in bioinformatics, computational biology, distributed computing, and cloud-based scientific software.

Negotiation