Data & AI Engineer

About Us

AsiaVerify is a Singapore-based regulatorytechnology company delivering corporate verification and risk intelligence fororganisations operating across Asia. Our products power KYB, UBO, AML, andmerchant onboarding workflows, sourced directly from official companyregistries across 14 APAC jurisdictions and delivered through a Unified API andPortal.

Our platform sits on a large and growing baseof registry, ownership, and transaction data. Turning that data intodecision-ready, trustworthy output — and into AI-agent-accessible tools— is core to how we compete.

The Role

We're looking for a Data & AI Engineerto join our Product & Tech team, working across two connected areas: dataanalytics on our transaction and registry data, and AI engineering on the toolsand platforms that let AI agents and internal assistants use that datareliably.

This is not a narrow reporting role or anarrow LLM-wrapper role.

You'll monitor and reconcile livetransaction and registry data to catch anomalies before they're misread astrend, and you'll build and own the tooling that lets AI agents query ourdata correctly and safely.

The split between the two areas isn't fixed atthe outset — it will be shaped around actual workload once you're ramped up.You'll pair with a senior team member on the data side first before taking onsolo ownership; AI engineering work can start near-immediately if you alreadyhave relevant experience.

Responsibilities

Data & Analytics

• Support live transaction health monitoring,and maintain/extend order-volume trend reporting by method, product, andcountry

• Flag transaction-level anomalies (e.g.a single client's volume swing skewing a daily trend) and route them forsanity-checking with commercial/CS before they're read as organic movement

• Support weekly infrastructure anddata-source reliability monitoring

• Cross-reference and reconcile ownership/shareholderdata against reported figures, clearly labeling computed vs.source-reported values

• Support market-stabilization trackingfor newer jurisdictions — completion rates, resolution times, and root-causeflagging on data-source-level issues

• Continuously improve the tooling and reportingpipeline itself, rather than only running it manually

AI Engineering

• Own the quality and reliability of our MCP(Model Context Protocol) server — the interface that lets external AIagents call our verification data directly — including tool design, security,and test coverage

• Refine agent-facing tool descriptions andinput schemas so agents select the right tool and construct valid calls,backed by observability into real call traffic, failures, and retries

• Own quality and performance for our AI-poweredcompany search tool — tuning retrieval and query strategy per market, andowning the security layer that prevents fetched content from steeringthe model, leaking prompts, or injecting fabricated claims

• Manage integrations with third-party dataand model APIs that power AI search

• Build and ship agent workflows for ourinternal AI assistant, own the model-provider adapter layer (balancing cost,latency, and quality), and iterate based on usage data and user feedback

• Support model and prompt optimizationacross AI-driven product surfaces, balancing cost against output quality

Requirements

• Degree in Computer Science, Data Science,Engineering, or a related field

• Strong SQL and Python skills, withhands-on experience building data pipelines, reports, or dashboards from realproduction data

• Practical experience building with LLM APIs(e.g. Claude, OpenAI) — prompt design, evaluation, and iterating based on realoutputs rather than one-off demos

• Understanding of retrieval/search systemsand how to evaluate answer quality and relevance

• Comfortable working directly with messy,real-world data — reconciling numbers across sources, spotting anomalies,and being explicit about what's computed vs. sourced

• Strong written communication — able todocument scope, flag risk, and hand off work clearly to non-technicalstakeholders

Nice to Have

• Experience with the Model Context Protocol(MCP) or building tools for AI agents

• Exposure to LLM evaluation frameworksor systematic prompt/output testing

• Familiarity with KYB / KYC / AML / UBOor other regulatory-data domains

• Prior internship or project experience withAsiaVerify's data or product surfaces

What We'reLooking For

• Someone who can move between structuredanalytics work and more exploratory AI-tooling work without needing the scopefully fixed in advance

• A fast learner who's comfortable pairingclosely with a senior engineer at first, then owning a workstream independently

• Comfortable working in environments where:

o Scope shifts as workload becomes clearer

o Data integrity and security are first-orderconcerns, not afterthoughts

o Untrusted content must never be allowed tosteer an AI system

Location& Working Arrangements

• Location: Singapore (Hybrid)

• Full-time (Monday to Friday)