Software Engineer - AI

Location: Singapore

Company

hirify.global is a fast-growing fintech company headquartered in Singapore, building responsible credit and financial products for underserved individuals and small businesses across Southeast Asia and other markets.

What you will do

• Design, build, deploy, and operate production AI applications, backend services, APIs, integrations, and LLM-powered agent workflows.
• Own delivery end to end, including requirements clarification, architecture, implementation, testing, deployment, troubleshooting, and continuous improvement.
• Use AI coding agents to prototype and implement changes while maintaining accountability for security, design, and production quality.
• Measure and improve application quality using tests, traces, observability, user feedback, and LLM or agent evaluations.
• Turn successful internal AI patterns into documented, reusable platform components.
• Collaborate with engineering, product, security, data science, business, and internal user teams on AI platform adoption.

Requirements

• 3+ years of professional software engineering experience, including hands-on Python development for production backend services or APIs.
• 2+ years of experience with relational databases such as PostgreSQL or MySQL, including schema design, SQL, indexing, and query-performance analysis.
• 2+ years of experience deploying, operating, and monitoring backend services on AWS or GCP with Docker or Kubernetes and CI/CD pipelines.
• Hands-on experience building LLM-powered applications with agents, tools, and multi-step workflows, including areas such as RAG, evaluations, guardrails, streaming, or agent frameworks.
• Experience using AI coding agents such as Claude Code or Codex for prototyping, implementation, testing, failure investigation, and code review.
• Strong problem-solving, communication, and cross-functional collaboration skills.

Nice to have

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
• Experience scaling LLM platforms for 1,000+ active users and managing latency, concurrency, reliability, and cost.
• Knowledge of emerging LLM capabilities, MCP/A2A, agent memory, evaluation, safe code execution, model routing, streaming, or fine-tuning.
• Experience building enterprise knowledge-access and retrieval systems with relevance, source attribution, and access permissions.
• Experience with production model adaptation and serving, including SFT, LoRA, DPO, RLHF, GRPO, distillation, quantization, or vLLM.

Culture & Benefits

• Hands-on ownership of meaningful parts of an internal AI transformation platform.
• Work in a fast-moving environment with ambiguous requirements and opportunities to ship quickly.
• Collaborate across engineering, research, product, security, data science, business, and user teams.