Junior GenAI Engineer

Role overview Join an engineering team building production generative AI and agentic systems for business use cases in financial services and retail. This entry-level role pairs a recent or soon-to-be graduate with experienced engineers, data scientists, and an architect, with structured support toward a full GenAI Engineer position.

Responsibilities - Help build and test agent workflows, including planning, memory, and state handling, primarily with LangGraph. - Write and maintain Python code for language model integrations, prompts, and tool calling. - Contribute to retrieval-augmented generation pipelines, including chunking, embeddings, and vector store connections. - Measure agent accuracy, speed, cost, and hallucination rates with observability tools, and document findings. - Assist with cloud deployment tasks and prepare tests, technical documentation, and demos. - Take part in code reviews, sprint planning, knowledge sharing, and regular study of emerging frameworks.

Requirements - A completed degree, or one expected within six months, in computer science, software or data engineering, AI/ML, or a related field. - Solid Python skills and familiarity with Git, debugging, and writing and reading tests. - Hands-on exposure to generative AI or agent development; the source’s detailed technology requirements are incomplete.

Nice to have - Experience with a cloud platform, especially Vertex AI, and a vector database such as Pinecone, Weaviate, Chroma, or pgvector. - Familiarity with agent protocols or development kits, including A2A or ADK. - A relevant thesis, competition entry, open-source contribution, or personal project.

Benefits and work setup - Permanent role with remote-friendly options in Bangkok, Hong Kong, Singapore, or remotely. - Named mentor, real client work from the start, and a performance-based route to a full GenAI Engineer role. - Entry-level compensation, medical insurance, and sponsored team events.