Staff Engineer I

At Backbase, we build comprehensive payments functionality into our platform to empower banks worldwide. As a Technical Domain Expert (Staff Engineer Level), you are THE trusted technical authority for our broad payments business domain. Your primary leverage is acting as a force multiplier, applying your deep technical expertise and extensive Payments Domain knowledge to enable teams and deliver value in a complex business and technical domain.

Payments Domain Expertise

Extensive functional and technical knowledge of global payment rails, specifically covering US, European, and Asian markets.

Deep understanding of payment workflows, compliance, and processing tailored for both Retail banking and SME/Commercial sectors.

Meet the Job: Key Responsibilities

The Solver: Parachute into the hardest technical challenges spanning multiple teams to remove volatility and ambiguity.

Design Ownership: Own high-level design for multi-service capabilities, ensuring security and scalability are embedded from the start.

Technical Project Leadership: For large strategic initiatives, you step in as the technical lead, driving the architecture and execution strategy across multiple engineering teams.

Core Systems Prototyping: Write the complex cores and skeletal systems that other teams build upon..

Execution Focus: You ensure the current quarter is executed with technical excellence.

Bar Raising: Serve as the primary approver for critical-path design reviews and major technical initiatives.

Technical Mentorship: Act as a dedicated mentor and coach for engineers, guiding their technical growth, fostering a high-performance culture, and helping to cultivate future technical leaders.

AI-Native Engineering & AI Agent Governance

AI Adoption: Lead the adoption of agentic tooling, and AI automation within your team to accelerate the development lifecycle.

Tooling & Governance: Skill in selecting, configuring, and governing the use of AI tooling.

Context Engineering: Advanced skill in configuring, governing, and providing detailed, context-rich inputs for AI agents.

Harness Engineering: Advanced skill in engineering the AI agent's operational environment (the 'harness'), ensuring it includes the necessary security, retrieval, and validation systems for reliable, high-quality code generation.

Auditing & Validation: Crucially, the ability to validate and correct AI output for correctness, compliance with standards, and security before integration. The paramount skill is healthy skepticism and the ability to critically review and validate AI-generated code.

Hard Skills: Deep Software Engineering Foundation

As a modern AI-First Engineer, you are a deeply grounded software professional who leverages AI agents and tools to amplify productivity and quality, not as a replacement for fundamental engineering principles.

Code & Architecture: Deep understanding and strict application of Clean Code principles, alongside mastery of SOLID principles to ensure maintainable, extensible codebases.

Design Patterns: Expertise in classic Design Patterns and modern architectural patterns like Microservices, Event-Driven Architecture, and Serverless computing.

Domain-Driven Design (DDD): Ability to apply Domain-Driven Design principles, including defining Bounded Contexts, Ubiquitous Language, and Aggregate Roots, to model complex business domains effectively.

Testing & Quality: Advanced practice of Behavior-Driven Development (BDD) and Test-Driven Development (TDD), ensuring that requirements are defined by tests and implementation follows.

DevOps & Infrastructure: Expertise in Continuous Integration and Continuous Deployment (CI/CD) pipelines, infrastructure-as-code (IaC), and modern DevOps practices for automating the software delivery lifecycle.

You have years of experience with a strong track record in designing and delivering complex software systems.

You have a T-shaped skill profile, possessing deep expertise in one area with broad competence across the full stack.

You excel at "Influence Without Authority," shaping decisions across teams through expertise and persuasion.

You are highly craft-focused and proactive in addressing cultural and technical debt.

System Thinking: The ability to view the software product as a complete system, understanding how AI-generated components interact with existing infrastructure, security models, and deployment pipelines.

Architectural Vision: The capacity to hold the overall system design in mind, ensuring that the piecemeal, task-oriented output from AI agents aligns with the long-term architectural goals and scalability requirements.

Communication: Exceptional clarity in communication, especially when defining requirements for AI agents and explaining the rationale for modifications to AI-generated solutions to human team members.