• Research and formalize HKEX-listed-company disclosure requirements into machine-readable knowledge structures, including document taxonomies, disclosure routes, issuer-data models, clause logic, approval workflows, exception handling, and validation frameworks for AI-assisted automation.
• Design structured questionnaires, decision trees, rule engines, and retrieval logic that enable AI systems to determine document type, required inputs, disclosure pathways, clause selection, template assembly, and exception-handling requirements.
• Define reusable variables, metadata schemas, issuer profiles, knowledge assets, controlled vocabularies, and data structures for implementation within AI-enabled CMS/SaaS platforms, retrieval-augmented generation (RAG) workflows, and rule-based document automation systems.
• Define how AI can support structured drafting, clause selection, field extraction, normalization, consistency checks, and first-pass assembly while preserving deterministic validation rules and human review.
• Translate research findings into developer-readable requirements, user-flow specifications, data-model requirements, test cases, and prototype logic for the engineering team.
• Maintain structured R&D records covering research assumptions, sample disclosures, taxonomy decisions, test outputs, technical uncertainties, design decisions, and findings for internal review and potential funding-related reporting.
• Collaborate with the CTO, developers, knowledge engineering stakeholders, and downstream publishing, QA, localization, and Layout Engineering teams. The role remains focused on R&D, system logic, and specifications, not routine production work.

• Master's degree or doctoral degree preferred in a STEM-related discipline with strong finance, FinTech, regulatory-reporting, or financial-technology relevance. A strong bachelor's degree may be considered where the candidate has exceptional practical R&D or system-development experience.
• Master’s degree or doctoral degree in a STEM-related discipline from a local or internationally recognized university ranked within the top 100 in STEM subjects (as per QS, ARWU, THE, or USNWR rankings). A strong bachelor’s degree may be considered if the candidate demonstrates exceptional practical R&D or system-development experience and meets the STEM discipline requirement.
Relevant fields include Financial Technology, Financial Engineering, Quantitative Finance and FinTech, Financial Technology and Data Analytics, Financial Technology and AI, Business Information Systems with financial technology focus, Artificial Intelligence, Data Science, Information Systems, Computational Linguistics, Knowledge Engineering, or other related STEM disciplines.
• Relevant fields include Financial Technology, Financial Engineering, Quantitative Finance and FinTech, Financial Technology and Data Analytics, Financial Technology and AI, Business Information Systems with financial technology focus, Artificial Intelligence, Data Science, Information Systems, Computational Linguistics, Knowledge Engineering, or related STEM disciplines.
• Strong understanding of financial markets, listed-company disclosure, regulatory reporting, banking technology, corporate actions, ESG/sustainability reporting, announcements, circulars, issuer data, or regulated financial-document workflows.
• Ability to transform complex financial or regulatory information into structured taxonomy, data models, route logic, variables, clauses, validation rules, and exception paths.
• Ability to write clear technical documentation, research notes, system specifications, and developer-readable requirements in English.
• Practical understanding of AI-assisted workflows beyond chatbot use, including structured outputs, prompt logic, rule-based checks, human-in-the-loop review, and validation guardrails.
• Strong analytical, structured, and systems-thinking ability, with the capacity to design workflows, decision trees, data structures, validation logic, and
CMS/SaaS configuration requirements.

Duties and Responsibilities: • Layout and update Annual Reports, prospectuses, and other investor-relations documents in Adobe InDesign • Handle multi-round revisions, data updates, and late-night submission changes with full accuracy • Ensure formatting compliance with PSE, HKEX and SGX disclosure standards • Maintain style consistency across tables, charts, and appendices • Implement edits from project managers, auditors, translators, and legal teams • Assist in building internal templates and best-practice guides for financial typesetting • Support pre-press preparation and file delivery for both print and digital outputs • Provide feedback on workflow optimization, automation, and quality-control tools

We are looking for: a skilled Financial Typesetter / Layout Specialist to produce high-accuracy, financial documents such as Annual Reports, IPO prospectuses, and ESG reports. This is not a general graphic-design position. You will work on regulated financial publications where numbers, tables, and disclaimers must be precise, consistent, and compliant. You will collaborate with client-facing managers, translators, and designers to ensure perfect alignment across versions and languages. Ideal candidates come from financial printing firms or investor-relations design agencies and understand how to balance speed, accuracy, and version control under pressure.

Gradient Force Technologies seeks a proactive HR Specialist / Recruiter to drive overseas talent acquisition across Southeast Asia, supporting regional expansion.
Key Responsibilities
• Manage end to end recruitment: sourcing, screening, interviews, offers.
• Focus on Southeast Asia (Philippines, Vietnam, Thailand, Malaysia, Indonesia).
• Partner with hiring managers to design recruitment strategies.
• Build pipelines via job boards, social media, agencies.
• Support technical/engineering hiring, especially semiconductor roles.
• Coordinate cross border hiring and onboarding.
• Provide limited HR/admin support (~20%) for Hong Kong office.
• Collaborate with regional teams for international hiring needs.

• 2–5 years in HR/recruitment, preferably overseas markets.
• Strong advantage: Malaysian market and semiconductor industry experience.
• Fluent in English & Chinese; strong cross cultural communication.
• Organized, adaptable, able to manage multiple processes.
• Willing to travel (Shanghai, Penang).

Job Summary
We are looking for a Full Stack Agentic AI Engineer to build end-to-end autonomous systems. You will be responsible for designing the cognitive architecture of AI agents, building the high-performance backends that allow them to execute tools, and crafting frontends that visualize complex AI reasoning steps in real-time. You aren't just building an app; you are building a collaborative partner for our users.
1. AI Description
● Agent Orchestration: Build multi-agent workflows using frameworks like LangGraph, CrewAI, or Semantic Kernel.
● Reasoning Patterns: Implement advanced patterns like ReAct (Reason+Act), Plan-and-Execute, and Reflexion loops to minimize hallucinations.
● Memory & RAG: Architect long-term memory systems using Vector Databases (Pinecone, Milvus) and Retrieval-Augmented Generation (RAG) to ground agent actions in company data.
● Tool Integration: Use the Model Context Protocol (MCP) to securely connect agents to internal databases, Slack, GitHub, or third-party APIs.
2. Backend
● Async Infrastructure: Develop high-concurrency backends using Python (FastAPI) or Node.js to handle long-running agent tasks without blocking the UI.
● AgentOps & Observability: Implement tracing and monitoring (e.g., LangSmith, Arize Phoenix) to debug why an agent made a specific decision.
● Guardrails: Build deterministic "fallback" logic and safety layers to intercept and correct unintended agent actions before they hit production.
3. Frontend
● Streaming Interfaces: Build responsive UIs (React, Next.js) that stream "Thinking" states, tool-use logs, and incremental results to the user.
● Human-in-the-Loop (HITL): Design "Approval" UI components where agents pause and wait for human confirmation before taking high-stakes actions.
● Collaborative UX: Create dashboards that visualize multi-agent collaboration (e.g., showing a "Researcher" agent handing off data to a "Writer" agent).

Technical Requirements
● Languages: Expert-level Python (for AI/Backend) and TypeScript (for Frontend/API safety).
● Frameworks: LangGraph/LangChain, React/Next.js, FastAPI.
● Databases: Proficiency in both relational (PostgreSQL) and Vector (Weaviate, Chroma) databases.
● Cloud/DevOps: Experience with Docker/Kubernetes and AI-specific deployments (Azure AI Foundry, AWS Bedrock, or Vercel AI SDK).
Preferred Qualifications
● Contributions to open-source agentic projects.
● Experience with Small Language Models (SLMs) for low-latency, on-device agent tasks.