What are the responsibilities and job description for the Senior AI Engineer position at workatbackbase?
Backbase is on a mission to help banks re-architect around the customer and embrace the era of Engagement Banking. We are looking for a Senior AI Engineer to join our AI & Automation team. In this role, you will be at the forefront of the banking revolution, building sophisticated AI assistants and agentic platforms that redefine how customers interact with their financial institutions.
The Role
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.
Key Responsibilities
- 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.
Technical Requirements
- 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.
Why Backbase?
At Backbase, you’ll work in an environment that values innovation over bureaucracy. You will have the opportunity to own the AI lifecycle from ideation to global deployment, impacting millions of banking customers worldwide.