Applied AI Engineer, Agentic Analytics Platform

Location: Singapore; hybrid work with at least 3 days in the office, with exact expectations confirmed by the Hiring Manager.

Company

hirify.global is a global payments technology company serving consumers, merchants, financial institutions, and government entities in more than 200 countries and territories.

What you will do

• Build and extend a full-stack analytical agent for exploring, analyzing, visualizing, and explaining financial and transaction data in natural language.
• Design agent workflows covering data retrieval, SQL generation, validation, narrative generation, visualization, tool calling, retries, timeouts, cancellation, and human-in-the-loop controls.
• Develop and maintain the business knowledge layer, trusted analytical data, evaluation suites, benchmark datasets, acceptance criteria, and regression coverage.
• Build Python services, Node.js APIs, and React/TypeScript interfaces, including asynchronous and stateful workflows that are observable, testable, and maintainable.
• Integrate with enterprise identity and data platforms while supporting access control, logging, rate limiting, privacy, reliability, and responsible AI practices.
• Work with internal users to define requirements, demonstrate the product, collect structured feedback, and provide guidance on prompting and generative AI workflows.

Requirements

• Bachelor’s degree in a quantitative or technical discipline, or equivalent practical experience.
• 3–6 years of experience building analytical applications, data workflows, or AI-powered products, or equivalent demonstrated capability.
• Strong production experience with Python and SQL, including testing, logging, debugging, relational data modeling, and data reconciliation.
• Hands-on experience building LLM-powered applications with instruction design, tool calling, structured outputs, context management, and failure or hallucination handling.
• JavaScript or TypeScript literacy and the ability to make scoped changes across APIs and web interfaces.
• Software-engineering fundamentals including Git, code review, unit and integration testing, REST APIs, relational databases, documentation, production troubleshooting, and enterprise data access controls.

Nice to have

• Experience with React, Node.js, Express.js, Temporal, Docker, OAuth, single sign-on, authorization, or observability tooling.
• Familiarity with model-provider SDKs, Model Context Protocol, evaluation and tracing platforms, or multi-agent systems.
• Experience evaluating text-to-SQL or other nondeterministic AI systems.
• Experience with Plotly, Matplotlib, pandas, NumPy, Spark, or comparable analytical and distributed-processing tools.
• Experience in banking, payments, financial services, or other regulated, data-intensive environments.

Culture & Benefits

• Work on a live production system with real internal users rather than a pilot.
• Own defined technical workstreams end to end, from business questions to shipped and trusted answers.
• Collaborate with data, platform, security, product, and regional business partners.
• Contribute to a modern agent stack involving LLM orchestration, business knowledge, text-to-SQL, durable workflows, and evaluation practices.