Lead Data Engineer

C++ Engineer - Market Data

Ho Chi Minh, Ha Noi - Viet Nam

Product

Maintain/enhance our legacy C++-based tick data processing platform as needed, demonstrating product ownership, and helping migrate datasets to our new tick data processing platform. Contribute to our new, modern C++-based tick data processing platform - enhancing the platform to support additional tick data feeds across asset classes, developing/reviewing the implementation of tick data-based interval features/statistics, and adding new functionality to the platform all while maintaining high software standards and best practices. Collaborate with the Research and Portfolio Management organizations to facilitate the transition from our legacy platform to our new platform, supporting their price volume data needs for signal generation.

Negotiation

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 client 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

Head 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