AI Engineer

HYDRAX DIGITAL ASSETS PTE. LTD.; Singapore; On-site; SGD 100,000 - 160,000; Full time

Job summary

HYDRAX DIGITAL ASSETS PTE. LTD. is seeking an AI Engineer to design, deploy, and operate AI systems used across compliance, onboarding, and operations within a regulated financial setting. You will build production-grade pipelines and manage end-to-end ML workflows.

You will work with Python, orchestration frameworks, vector stores, and model APIs, ensuring robust guardrails, logging, and governance for regulatory compliance.

Qualifications

• Bachelor's degree or 3+ years as AI engineer/scientist.
• Experience deploying AI systems to production beyond prototypes.

Responsibilities

• Build, deploy and optimise AI systems in production.
• Design and implement retrieval-augmented generation pipelines and multi-agent orchestration.

Skills

Python

LangGraph

CrewAI

Vector databases

Model APIs

CI/CD

Cloud deployment

Education

Bachelor's degree in CS/IT/Programming

Tools

LangGraph

CrewAI

Vector databases

Model APIs

CI/CD

Job description

Hydra X is hiring an AI Engineer to build and operate the AI systems used across compliance, client onboarding and operations. This is a hands-on engineering role. You will design, deploy and evaluate AI systems running in production inside a regulated financial institution.

Key responsibilities

• Build, deploy and optimise AI and machine learning systems in production, including for scale, latency and cost.
• Build pipelines for the extraction, transformation and loading of large volumes of unstructured data, including regulatory documents, client records and operational logs, into retrieval and inference workflows.
• Implement retrieval-augmented generation pipelines: document curation, category filtering, relevance scoring and citation controls, so that outputs are traceable to authoritative sources.
• Design multi-agent orchestration and human-in-the-loop routing for workflows subject to regulatory approval gates.
• Run experiments to test the performance of deployed models. Build and maintain evaluation frameworks covering task completion, error rates and human handoff rates, and failure-mode testing for hallucination, prompt injection and boundary violations.
• Diagnose and resolve defects arising in deployed systems.
• Work with the infrastructure on which models are deployed, including orchestration frameworks, vector stores, model APIs and cloud services.
• Implement guardrails, immutable audit logging and role-based access controls appropriate to a regulated environment.
• Work with compliance, operations, product and engineering colleagues to specify requirements and move systems from prototype into production.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Programming and Systems Analysis, or Science (Computer Studies). Alternatively, a minimum of three years of work experience as an AI engineer, AI researcher or AI scientist.
• Demonstrated experience building and deploying AI systems into production, not prototypes alone.
• Proficiency in Python, with experience in orchestration frameworks such as LangGraph or CrewAI, vector databases, and commercial model APIs.
• Experience designing evaluation and failure-mode testing for AI systems.
• Working knowledge of cloud deployment, infrastructure as code and CI/CD.
• Experience delivering software under regulatory requirements is an advantage.