1 month ago
Singapore, SingaporeMid Level
Responsibilities
- Build AI applications, APIs, reusable components, and Python services using AWS AI and cloud-native services.
- Develop Generative AI, Agentic AI, RAG, prompt-based, workflow automation, and document intelligence solutions.
- Use AWS Bedrock, AgentCore, Textract, Comprehend, OpenSearch, Lambda, and related services in AI pipelines.
- Integrate AI outputs with enterprise APIs and downstream business systems, including data transformation and output validation.
- Contribute to shared reuse libraries, documentation, code reviews, and engineering productivity improvements.
- Apply security, governance, PII handling, content filtering, audit logging, AWS tagging, and cost-management practices.
- Collaborate with Cloud Engineering teams to deliver secure, scalable, and reliable solutions.
- Participate in technical discussions, design sessions, knowledge sharing, and relevant AWS and AI certification development.
Requirements
- 2–3 years of software or AI engineering experience, including professional or significant project or internship work building AI/ML systems.
- Ability to write clean, structured, and testable Python code independently.
- Practical experience with AWS services such as Lambda, S3, API Gateway, Bedrock, AgentCore, Textract, or SageMaker.
- Understanding of REST API development and consumption using FastAPI, Flask, or an equivalent framework.
- Practical familiarity with LLMs, RAG, prompt engineering, embeddings, and vector stores.
- Experience with AWS Bedrock model invocation and prompt engineering through an API.
- Exposure to document processing pipelines, PDF extraction, OCR, and extracting structured data from unstructured documents.
- Familiarity with vector databases or semantic search, such as Pinecone, OpenSearch, or pgvector.
- Experience with Git, branching, pull requests, code review, CI/CD, and documentation practices.
- AWS Cloud Practitioner or Developer Associate certification, or active progress toward one.
- Exposure to financial services or regulated data environments and genuine interest in AI engineering.