AI Engineer (Fintech)

TL;DR

AI Engineer (Fintech): Building and optimizing an "AI Operating System" for a high-growth Fintech, focusing on "Stateful" Agentic Systems and Multimodal RAG pipelines that can reason across text, charts, and financial tables. Focus on developing core generative capabilities, deploying them efficiently and securely, and architecting solutions bridging the AI tech stack with an enterprise data lake on AWS.

Location: Singapore, Central, Singapore

Company

hirify.global is a financial technology company providing a global network for real-time money movement around the world in over 130 countries and 80 currencies.

What you will do

• Architect and deploy production-grade RAG workflows and multi-step financial agents on cloud resources (AWS, GCP).
• Implement multimodal reasoning pipelines that ingest and reason over mixed-media financial documents.
• Design and perform adversarial testing (Red Teaming) for LLM vulnerabilities like Prompt Injection, Jailbreaking, and PII Leakage.
• Define, implement, and quantitatively evaluate AI models for faithfulness and relevancy using tools like DeepEval.
• Champion Deployment Autonomy by containerizing solutions (Docker) and deploying to cloud resources via GitLab CI.
• Ensure governance by implementing deterministic guardrails (NeMo Guardrails, Guardrails AI) to enforce JSON output schemas and block non-compliant financial advice.

Requirements

• 5+ years of total AI engineering experience, with 2+ years of hands-on experience building and deploying NLP or GenAI solutions in production.
• Multi-Cloud Fluency: Expertise in architecting solutions on major cloud platforms (AWS, GCP) and mastery of cloud-native LLM ecosystems (Bedrock, Vertex AI).
• Mastery of GenAI Orchestration: Expert-level skills in LangChain or LangGraph (specifically for stateful, multi-turn agents) or LlamaIndex.
• Proficiency with open-source tools for evaluation (DeepEval) and full tracing/observability (LangSmith, Langfuse, Arize Phoenix).
• Passion for MLOps: Ability to write GitLab CI pipelines (automated testing, linting, scanning) and strong Docker skills.
• Bachelor’s degree in a STEM field (Computer Science, Engineering, Mathematics, Physics).
• Python Expertise: Proficiency with data validation (Pydantic) and asynchronous REST APIs (FastAPI).
• Retrieval Engineering: Hands-on experience managing vector databases (Vertex AI Vector Search, Weaviate, Milvus or pgvector).
• Experience in Security & Red Teaming: Knowledge of adversarial testing frameworks (Giskard, PyRIT) for LLM vulnerabilities.

Nice to have

• Interest in the Fintech Industry, with prior experience in Payments, Banking, or Finance Services.
• Certifications: Google Professional Machine Learning Engineer / AWS Certified Machine Learning - Specialty.

Culture & Benefits

• Work in a high-growth Fintech environment with a startup mindset.
• Benefit from Deployment Autonomy, allowing you to architect, implement, test, and deploy your own solutions.