5 days ago
Singapore, SingaporeSenior
Responsibilities
- Architect production-grade RAG workflows on AWS or GCP using LangGraph or LlamaIndex and build agents for multi-step financial tasks.
- Implement multimodal reasoning pipelines for mixed-media financial documents including charts, graphs, and tables.
- Perform red teaming for prompt injection, jailbreaking, PII leakage, and other model vulnerabilities before systems access sensitive data.
- Define quantitative AI evaluation criteria and use tools such as DeepEval to measure faithfulness and relevancy and validate model upgrades and cost optimization.
- Containerize, test, and deploy solutions using Docker, GitLab CI, and cloud infrastructure.
- Implement deterministic guardrails with tools such as NeMo Guardrails and Guardrails AI to enforce JSON schemas and block non-compliant financial advice.
- Implement tracing, monitoring, and observability for generative AI systems.
Requirements
- 5+ years of total AI engineering experience, including 2+ years of hands-on experience building and deploying NLP or GenAI solutions in production.
- Expertise architecting solutions on major cloud platforms such as AWS and GCP, including cloud-native LLM ecosystems such as Bedrock and Vertex AI and services such as IAM and Storage.
- Expertise with LangChain, LangGraph, LlamaIndex, or equivalent orchestration tools for stateful, multi-turn agents.
- Experience with evaluation and monitoring tools such as DeepEval, LangSmith, Langfuse, and Arize Phoenix.
- Ability to write GitLab CI pipelines and strong Docker skills, including multi-stage builds.
- Bachelor’s degree in a STEM field such as Computer Science, Engineering, Mathematics, or Physics.
- Proficiency in Python, Pydantic, and asynchronous REST APIs such as FastAPI.
- Hands-on experience managing vector databases such as Vertex AI Vector Search, Weaviate, Milvus, or pgvector, with knowledge of indexing and chunking for hybrid search.
- Knowledge of adversarial testing frameworks such as Giskard and PyRIT for scanning LLM vulnerabilities.
- Fintech experience in payments, banking, or financial services is strongly preferred.
- Google Professional Machine Learning Engineer or AWS Certified Machine Learning - Specialty certification is highly preferred.
Tech Stack
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