Backbase
Senior AI Engineer
Join our Digital Engagement team in Vietnam
As a Senior AI Engineer, you will design, develop, and deploy scalable AI-driven solutions. You won't just be "prompt engineering"; you will be building the underlying infrastructure, agent orchestration layers, and evaluative frameworks that make AI reliable, safe, and impactful in a highly regulated financial environment.
What you'll do
Agentic Orchestration: Design and implement complex agentic workflows and assistant platforms using the LangChain ecosystem.
Advanced Retrieval: Develop and optimize RAG (Retrieval-Augmented Generation) and GraphRAG pipelines to provide agents with deep, contextual domain knowledge.
System Design: Architect scalable, distributed AI services that integrate seamlessly into our existing Kubernetes (K8s) environments.
Agentic Ops (AIOps): Implement robust monitoring, tracing, and evaluation frameworks (LangSmith, LangFuse, Promptfoo) to ensure the reliability and performance of LLM applications.
Skill Integration: Build and manage "Skills" and toolsets for agents, including the implementation of the Model Context Protocol (MCP) for seamless data/tool interaction.
Human-in-the-Loop (HIL): Design sophisticated HIL patterns to ensure high-stakes financial decisions remain governed and accurate.
Mentorship: Provide technical leadership to junior engineers and contribute to the internal AI strategy and best practices.
Who you are
Expertise in LangChain: Deep, hands-on experience with the LangChain ecosystem (LangGraph, LangServe) for building production-grade LLM applications.
Agentic Mastery: Proven track record of building autonomous agents or sophisticated assistant platforms using modern techniques (Tools, Skills, MCP).
AI Infrastructure: Strong knowledge of RAG architectures and emerging GraphRAG methodologies.
Python Proficiency: Expert-level Python skills with a focus on writing clean, maintainable, and asynchronous code.
System Architecture: Demonstrated ability to design and manage scalable, distributed systems within a Kubernetes ecosystem.
Observability & Evaluation: Experience using Agentic Ops platforms like LangFuse, LangSmith, or Promptfoo for debugging and performance tuning.
Strong Pluses
Java Knowledge: Experience with Java is a significant advantage, particularly in integrating AI services with Backbase’s core Java-based backend.
DevOps Culture: Familiarity with CI/CD pipelines, and cloud-native logging/monitoring.
Fintech Experience: Understanding of the security and compliance requirements unique to the banking and financial services industry.
Our Tech Stack
Languages: Python (Primary), Java (Secondary).
Frameworks: LangChain, LangGraph, FastAPI.
Ops/Tools: LangSmith, LangFuse, Promptfoo, MCP.
Deployment: Docker, Kubernetes, AWS/Azure.