Role Purpose

As a Senior Backend Software Engineer (Fixed Term Contract) within Boku’s Engineering organisation, you will be one of a small group of engineers delivering new products as part of Boku’s Innovation department. A new suite of products being built from the ground up. This is a greenfield development engagement: the work is scoped to designing and building new software, not maintaining or extending existing production services. You will work in a small, high-autonomy team with a clear remit and a defined delivery horizon, reporting to the Head of Product and Engineering.

Key Responsibilities

Backend Engineering

• Design and build production-grade services using Java and Spring Boot, targeting high throughput, low latency, and high availability (99.99%+).
• Implement and evolve RESTful/gRPC/MCP and event-driven APIs supporting payment initiation, callback handling, reconciliation, and settlement flows.
• Build for fault tolerance and resilience: circuit breakers, retry logic, idempotency, and graceful degradation under load. Maximum observability and telemetry at the core of the build to ensure easy support.
• Optimise service performance through profiling, load testing, and careful data access layer design (SQL and NoSQL).
• Collaborating with colleagues and off-shore development teams providing code-reviews and guidance as necessary to team members and development studios.

Payment Systems

• Build the core components of Payout, Card Processing and FX systems from scratch, including a payout processing engine, AI agent treasury orchestration layer, and cash forecasting service. This work is entirely new development and there is no existing codebase to maintain or inherit.
• Contribute to PCI DSS compliant system design and implementation, including sensitive data handling, audit logging, and access control.

Frontend Contribution

• Contribute React-based frontend components for internal tooling, operational dashboards, and merchant-facing interfaces where required.
• Work with Product and Design to deliver functional, well-tested UI features that meet Boku's quality bar.

FX & Treasury Integration (Desirable)

• Support integration with FX data sources including Bloomberg feeds, for use in real-time rate pricing, settlement FX, and treasury risk tooling.
• Contribute to cash position and FX exposure monitoring services, working alongside Finance and Treasury stakeholders.

Reliability & Operations

• Instrument projects with observability from day one: structured logging, distributed tracing, metrics, and alerting built as part of the product, not retrofitted. On-call and incident management for existing Boku production services are outside the scope of this contract.
• Instrument services with structured logging, distributed tracing, and metrics; contribute to SLO/SLA definitions and alerting.
• Set up CI/CD pipelines, container build configuration (Docker/EKS), and code quality gating (SonarCloud, SAST) as new infrastructure built to Boku’s engineering standards and handed over as part of the finished product.

Key Skills, Experience and Competencies

Required

• 5+ years of backend engineering experience, with deep expertise in Java and the Spring Boot ecosystem (Spring MVC, Spring Data, Spring Security).
• Demonstrable experience building and operating high-throughput, high-availability distributed payment or financial services systems.
• Strong understanding of payment system architecture: idempotency, exactly-once delivery, reconciliation, and settlement flows.
• Experience with relational databases (PostgreSQL, MySQL) and messaging systems (Kafka, RabbitMQ, or equivalent).
• Familiarity with container-based deployment (Docker, Kubernetes/EKS) and CI/CD pipeline tooling (GitHub Actions or equivalent).
• Experience with PCI DSS compliant system design and secure coding practices.
• Strong communication skills; ability to work effectively with Product, Architecture, and Operations in a globally distributed team.

Preferred

• React frontend development experience sufficient to contribute to internal tooling and dashboards.
• Experience integrating with Bloomberg data feeds (BFIX, B-PIPE, or similar) or other real-time FX data sources.
• Background in FX processing, treasury systems, or multi-currency settlement.
• Experience with financial messaging standards (ISO 20022, SWIFT MT/camt formats).
• Prior work in a payments processor, PSP, or fintech operating across multiple markets.

AI & Agentic Systems

• Practical experience building or integrating LLM-powered features into production services, including prompt engineering, tool/function calling, and structured output handling via APIs such as Anthropic or OpenAI. Familiarity with AWS Bedrock is ideal.
• Experience designing or contributing to agentic workflows: multi-step autonomous processes where models plan, call tools, and act on results — including handling retries, failure modes, and human-in-the-loop checkpoints.
• Familiarity with MCP (Model Context Protocol) or similar tool-use frameworks for connecting AI models to internal APIs, databases, and external services.
• Comfortable using AI-assisted development tooling (e.g. Claude Code, GitHub Copilot, Cursor) as part of day-to-day engineering workflow, and able to reason critically about where AI assistance adds value versus where it requires human judgement.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 5+ years of professional software engineering experience in backend-heavy roles.
• Prior experience in a regulated financial services or payment processing environment strongly preferred.

Why Join Boku?

Impact: Work on payment infrastructure that processes billions of dollars annually, serving some of the world's largest digital commerce platforms across 65 countries.

Focus: A fixed term engagement with a clearly scoped remit, embedded within a high-calibre engineering team operating on greenfield and core platform work.

Culture: A collaborative, inclusive engineering culture that values craft, rigorous thinking, and delivery. Boku is a genuinely global company with deep expertise in local payment markets.

Benefits: Competitive day rate, flexible working arrangements, and Singapore-based team with global stakeholder exposure.

As a Backend Engineering Lead you'd be able to work on and solve many interesting challenges which we are facing, learn new ways of working, and help build delightful high quality products for our customers.  

Key Responsibilities

Technical Vision and Strategy

• Defines and communicates the technical vision and strategy for the engineering team, aligning it with overall business objectives.
• Evaluates emerging technologies and industry trends — including AI/ML capabilities, LLM-based tooling, and agentic frameworks — to inform technical roadmaps and architectural decisions.

Team Leadership and Mentorship

• Leads and mentors a team of engineers, fostering a culture of collaboration, innovation, and continuous learning.
• Provides guidance and support to team members, empowering them to grow both technically and professionally.
• Builds AI literacy across the team — ensuring engineers can effectively leverage AI-assisted development tools (code generation, automated review, test generation) while maintaining critical thinking about AI outputs.
• Coaches engineers on prompt engineering, AI pair-programming workflows, and when to trust vs. verify AI-generated code.

Project Management and Execution

• Manages technical projects from inception to delivery, overseeing planning, execution, and quality assurance processes.
• Coordinates with cross-functional teams, including product management, design, and QA, to ensure successful project outcomes.
• Incorporates AI-augmented estimation and planning tools where appropriate, while maintaining accountability for delivery commitments.

Architecture and Design

• Designs and implements scalable, maintainable, and extensible software architectures, considering factors such as performance, security, and scalability.
• Leads architectural discussions and collaborates with senior engineers to drive consensus on design decisions.
• Architects systems with AI integration patterns in mind — designing clean boundaries for AI/ML components, defining contracts between deterministic and probabilistic systems, and planning for model versioning, fallback strategies, and graceful degradation.

Technical Excellence

• Sets high standards for code quality, performance, and maintainability, and ensures adherence to best practices and coding standards.
• Conducts code reviews and provides constructive feedback to ensure the delivery of high-quality software solutions.
• Establishes guardrails and review standards for AI-generated code — ensuring it meets the same quality bar as human-written code, with particular attention to security, edge cases, and maintainability.
• Champions responsible AI practices: output validation, bias awareness, hallucination mitigation, and appropriate human-in-the-loop controls for critical paths.
  
  

Operational Ownership

• Takes end-to-end ownership of the systems the team builds — from deployment through production reliability, performance, and incident response.
• Drives operational maturity: SLOs/SLIs, alerting hygiene, runbook coverage, on-call readiness, and post-incident reviews that produce lasting improvements, not just action items.
• Ensures the team builds with production in mind from day one — observability, graceful degradation, and failure modes are first-class design concerns, not afterthoughts.
• Instils a "you build it, you run it" culture where engineers feel genuine accountability for what they ship and how it behaves under real-world conditions.

Problem-Solving and Decision-Making

• Demonstrates advanced problem-solving skills, leveraging deep technical expertise and critical thinking to address complex technical challenges.
• Makes informed decisions under uncertainty, weighing technical trade-offs and considering long-term implications.
• Knows when AI is the right tool for a problem and when it isn't — resists the pressure to "add AI" where simpler, more deterministic solutions are more reliable and cost-effective.
• Leverages AI-assisted analysis (log analysis, incident correlation, root cause detection) to accelerate debugging and reduce mean time to resolution.

Stakeholder Management and Communication

• Builds strong relationships with stakeholders, including product managers, business leaders, and other engineering teams, to understand requirements and priorities.
• Communicates technical concepts and project status effectively to both technical and non-technical stakeholders, adapting communication style as needed.
• Translates AI capabilities and limitations into business terms — sets realistic expectations around what AI can deliver, timelines for AI-powered features, and the ongoing cost of maintaining AI systems (compute, data quality, model drift).
• Educates stakeholders on the difference between demo-grade AI and production-grade AI, managing enthusiasm without stifling innovation.

Risk Management and Mitigation

• Identifies and mitigates technical risks proactively, anticipating potential issues and implementing contingency plans to minimize impact on project timelines and deliverables.
• Maintains a focus on security, privacy, and compliance requirements, ensuring that systems and processes adhere to relevant standards and regulations.

Continuous Improvement and Innovation

• Drives a culture of continuous improvement and innovation within the engineering team, encouraging experimentation, knowledge sharing, and adoption of new technologies.
• Promotes automation, tooling, and process enhancements to improve efficiency, reliability, and scalability of development workflows.
• Runs structured experiments with AI tools and workflows — measuring real impact on velocity, quality, and developer experience rather than relying on anecdotal evidence.
• Builds internal knowledge sharing around AI use cases, effective patterns, and lessons learned — creating a feedback loop that accelerates the team's AI maturity.
• Actively contributes to agentic AI workflows for automating repetitive engineering tasks (test generation, migration scripts, documentation, incident triage) while maintaining human oversight on critical decisions.
  
  

Leadership and Influence

• Leads by example, demonstrating integrity, accountability, and a commitment to excellence in all aspects of work.
• Inspires and motivates team members to achieve their full potential, fostering a positive and inclusive team culture.
• Positions the team as AI-forward without being AI-reckless — models the discipline of evaluating AI tools critically, adopting what works, and discarding what doesn't.
• Shapes the engineering organization's AI adoption narrative, contributing to company-wide standards, governance frameworks, and best practices for AI in production systems.

Role Specific Technical Competencies:

• Strong technical background in (AWS, Spring Boot, Kotlin, K8s, Microservices, Kafka, Istio, event-driven architecture).
• Exposure to Cloud Technologies, SRE (Site Reliability Engineering), and DevOps concepts with a focus on automation.

Our Ideal Candidate: 

• 10+ years of overall experience with the majority of this experience as an Engineering Lead or Manager.
• Experience working in Fintech / Financial organisations is an added advantage.
• At least 5 years of demonstrable leadership experience, at an individual team level and working across demographically distributed teams and organizational boundaries.
• Good experience in creating actionable strategies, with clear outcomes, and continuous measurement of progress.
• Ability to produce and communicate effective and insightful thought leadership on technical topics.
• Strong technical background in (AWS, Spring Boot, Kotlin, K8s, Microservices, Kafka, Istio, event-driven architecture).
• Exposure to Cloud Technologies, SRE (Site Reliability Engineering), and DevOps concepts with a focus on automation.
• Ability to take ownership and deliver results in a challenging client-facing environment.
• A degree in a relevant area of study would be helpful but not mandatory

What You’ll Be Doing

What We Look For In You 

Perks & Benefits

• Competitive total compensation package
• L&D programs and Education subsidy for employees' growth and development
• Various team building programs and company events
• Wellness and meal allowances
• Comprehensive healthcare schemes for employees and dependants
• More that we love to tell you along the process!