Why Verifone

For more than 30 years, Verifone has established a remarkable record of leadership in the electronic payment technology industry. Verifone is one of the leading electronic payment solutions brands and among the largest providers of electronic payment systems worldwide.

Verifone has a diverse, dynamic, and fast-paced work environment in which employees are focused on results and have opportunities to excel. We take pride in working with leading retailers, merchants, banks, and third-party partners to invent and deliver innovative payment solutions around the world. We strive for excellence in our products and services and are obsessed with customer happiness.

Across the globe, Verifone employees are leading the payments industry through experience, innovation, and an ambitious spirit. Whether it’s developing the next generation of secure payment systems or finding new ways to bring electronic payments to emerging markets, the Verifone team is dedicated to the success of our customers, partners, and investors. It is this passion for innovation that drives every Verifone employee toward personal and professional success.

Verifone is proudly an in-office work culture as we see immense benefits to career development and business results from our colleagues being physically co-located.

What’s Exciting About the Role

Verifone is seeking a Kafka DevOps Engineer to join our Platform Engineering team. This is an operations-first role with a strong emphasis on scripting, automation, and pipeline development. You’ll be hands-on with day-to-day Kafka operations, reliability, tuning, and high availability for payment gateway solutions that process billions of transactions annually on-prem and in AWS Cloud. Beyond keeping the lights on, you’ll play a key role in building the data pipelines—of which Kafka is a core component—that power Verifone’s new AI, machine learning, and analytics initiatives. You’ll also be part of an active effort to migrate Kafka and related services to Kubernetes, giving you hands-on experience with a meaningful infrastructure modernization project. The technology footprint is broad: Redis, MongoDB, PostgreSQL, MySQL, Snowflake, and more—so you’ll grow well beyond a single-technology niche.

Key Responsibilities

Kafka Operations & Reliability

• Manage and support Apache Kafka clusters (including MSK), Kafka Connect ecosystem, and KSQL for high-throughput, fault-tolerant messaging and event streaming pipelines.
• Monitor system health, set up alerts, and drive incident response and root cause analysis (RCA).
• Handle day-to-day operational tasks including offset management, lag monitoring, consumer group management, and cluster rebalancing.
• Perform routine cluster maintenance: upgrades, configuration changes, scaling, and health checks.

Scripting, Automation & DevOps

• Develop and manage automation scripts using Python and Shell scripting to reduce manual toil and improve operational efficiency.
• Design, implement, and maintain robust CI/CD pipelines for patching automation.
• Build and maintain Infrastructure as Code (IaC) using tools such as Terraform, Ansible, or similar.
• Containerize and orchestrate workloads using Docker and Kubernetes, with the opportunity to help migrate Kafka and related services to Kubernetes.

Data Pipeline Development

• Build and optimize end-to-end data pipelines, with Kafka as a core streaming component alongside batch and ETL processes, enabling new AI, ML, and analytics use cases.
• Collaborate with development teams to implement best practices for data flow, security, scalability, and performance.
• Continuously identify and implement improvements to the software development lifecycle (SDLC).

Cloud & Infrastructure

• Manage cloud infrastructure on AWS (VMs, networking, storage, IAM, etc.).
• Support cloud migration tasks and assist in moving workloads between on-prem and cloud environments.

Required Qualifications / Skills

• 4+ years of overall engineering experience with 2+ years of hands-on experience supporting Kafka infrastructure in a large-scale production environment.
• Kafka Producer/Consumer microservices concepts and Kafka distributed architecture.
• Solid Linux fundamentals: networking basics, logs, system troubleshooting, process/memory, disk.
• Strong scripting and automation skills (Python, Bash) with a track record of reducing operational toil.
• CI/CD pipeline development and Infrastructure-as-Code experience (Terraform preferred).
• Cloud engineering skills, preferably AWS (EC2, VPC, IAM, MSK/ElastiCache, CloudWatch).
• Familiarity with observability tools (metrics/logs/tracing concepts) and incident response practices.
• Basic understanding of distributed systems tradeoffs (availability, consistency, partitions, backpressure).
• Strong communication and presentation skills with emphasis on executive communication.
• Flexible with regards to working shifts; on-call and weekends.

Preferred Skills (Highly Desired)

Data Engineering & Pipelines

• Data engineering skills including data analytics, data processing, ETL, and data lake technologies (batch and streaming, file formats like Parquet, table formats like Iceberg/Delta/Hudi, basic orchestration).
• Experience with AWS data tools (Athena, Glue, Iceberg, Redshift, etc.).
• Exposure to Kafka Streams, Apache Flink, or similar stream processing frameworks.

Database & Caching Technologies

• Operate Redis deployments for caching, ephemeral state, queues/streams, and rate limiting use cases.
• Relational DB experience: PostgreSQL and/or MySQL (indexing basics, vacuum/analyze, query plans, replication fundamentals).
• MongoDB operational familiarity (replica sets, elections, oplog basics, backup/restore).

Infrastructure & Security

• Container/Kubernetes familiarity (deployments, stateful workloads, storage classes).
• On-prem experience (VMware/KVM, storage, networking).
• Security fundamentals: least privilege, secrets management, encryption-in-transit/at-rest concepts.
• Experience working with PCI (Payment Card Industry Data Security) standards.

What We Offer

• Direct impact on Verifone’s global payment infrastructure—your work keeps billions of transactions flowing reliably every year.
• Ground-floor involvement in building the data pipelines that will drive Verifone’s AI, machine learning, and analytics strategy.
• Hands-on participation in a Kafka-to-Kubernetes migration—a resume-building modernization project from day one.
• Multi-technology exposure—Kafka, Redis, MongoDB, PostgreSQL, MySQL, Snowflake—so you grow as a well-rounded platform engineer, not a single-tool specialist.
• Mentorship from senior engineers and Kafka architects with deep production experience.
• Clear career progression path from mid-level to senior and lead engineer.
• Funded certification paths—Confluent (CCDAK, Certified Administrator), AWS (Solutions Architect, MSK Specialty), CKA—plus budget for courses and technical conferences.
• Hybrid/remote working flexibility with a collaborative team culture.
• Competitive compensation with performance-based incentives.

Our Commitment

Verifone is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Verifone is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

The role

Our mission as the Payment Intelligence team is to augment our bank payments product with intelligent data products that differentiate our offering and increase our win rates.

Our focus areas are our existing products, Success+ and Protect+. This means creating market-leading payment recovery rates and fraud prevention products.

 Projects in the pipeline that align to these focus areas are:

• Improve payment recovery rates for failed Account to Account payments.
• Improve fraud detection rates of our ML models and rules based systems
• Improve the consumer authentication flow experiences for high risk payments.

As an engineer, you will be actively working on projects that help grow the adoption of these products while improving the experience of using the same and coming up with ideas for new product features in this space. You will be aided and supported in this journey by a team of super talented and motivated engineers.

This is a unique and high-profile opportunity for you, as an engineer, to work on building one one of GoCardless' major revenue streams in the coming years.

What excites you 

• You have a growth mindset, motivated by driving concrete business outcomes.
• You adapt to new technologies and processes quickly.
• You thrive in a collaborative environment and believe the best products are built through collaboration.
• You are passionate about building and improving products by experimenting, prototyping and applying an iterative approach to validate ideas and learn.

What excites us  

• You have strong programming experience with Ruby and/or Python
• You want to solve problems that will drive revenue growth and will have an impact on the engineering technical vision.
• You effectively collaborate with other engineering teams and business stakeholders. 
• You have a product ownership mindset and can work with other functions in the team to come up with ideas for product features.

Base salary range: 2,933–4,400 EUR gross

Base salary ranges are based on role, job level, location, and market data.  Please note that whilst we strive to offer competitive compensation, our approach is to pay between the minimum and the mid-point of the pay range until performance can be assessed in role. Offers will take into account level of experience, interview assessment, budgets and parity between you and fellow employees at GoCardless doing similar work.

About the Role:
We’re looking for a Backend Engineer to contribute to a next-generation security initiative. You’ll be part of a small, highly technical team working on novel approaches to secure systems - with a focus on cryptography, automation, and AI-powered analysis. You’ll work closely with senior engineers and contribute hands-on to the codebase across the stack. This role involves hands-on development, learning opportunities, and collaboration across engineering, product, and design.

Day to Day:

• Contribute to the design, development, and delivery of features across the product
• Write clean, maintainable code for back-end systems deployed in AWS or GCP
• Collaborate with AI and cryptography specialists
• Work with the product manager to understand requirements and help the team plan architecture, data flows, API specs, and testing strategies
• Follow established engineering practices and participate in team discussions around process and quality
• Participate in customer-driven development and iterate based on feedback
• Write automated tests for load, performance, and error handling

What you bring to the table:

• 3+ years of hands-on software engineering experience for backend development
• Excellent TypeScript and Node.js coding experience
• AWS experience in containers (EKS, ECS) and serverless systems
• Relational, key/value, and graph datastore experience with schema management
• API design, data modeling, secure service development, database systems
• Has a focus on quality code, error handling, and high availability
• A thoughtful, pragmatic approach to solving technical problems in a fast-paced environment
• At least upper-intermediate level of spoken and written English

Extra Credit:

• Versed in Python coding and environments
• Experience with GCP systems
• Experience with applied cryptography, especially key management, TLS, or post-quantum algorithms
• Familiarity with agent-based architectures or systems that scan and orchestrate actions across distributed environments
• Knowledge of AI/ML systems, particularly LLM integration or agent-style reasoning patterns
• Experience managing LLM agents to increase both speed and quality of code generation and tests
• Exposure to security tools, vulnerability detection platforms, or compliance automation
• Prior experience working on developer-facing or infrastructure-heavy products

What is this role about?

As the Lead Machine Learning Engineer at Bondora, you will be the backbone of our Data Science delivery. Your mission is to build the robust infrastructure that powers automated model pipelines, ensures deployment reliability, and governs the full ML lifecycle from experimentation to production.

This is a strategic and hands on engineering role. You will collaborate closely with Data Science, Data Engineering, and Development teams to remove friction, improve scalability, and bring stable, high quality ML solutions into everyday decision making.

You will guide the evolution of our ML engineering stack, lead high impact initiatives, and mentor engineers while shaping a culture of technical excellence 🌿

Your main responsibilities 🎯

• Guide the technical direction of Bondora’s ML engineering stack by selecting, evaluating, and implementing technologies, tools, and processes that improve scalability and reliability.
• Lead complex, high risk, or cross departmental projects that directly influence Data Science delivery, risk model performance, and production stability.
• Act as the bridge between Data Science, Data Engineering, and Development to identify and solve systemic technical challenges.
• Design and build advanced, production grade ML infrastructure and set the engineering standard for the team.
• Ensure all ML solutions are secure, observable, resilient, and scalable, following governance, compliance, and operational best practices.
• Mentor ML Engineers through code reviews, design sessions, and hands on technical leadership.
• Identify weaknesses or inefficiencies in model or data infrastructure and drive company wide improvements.
• Represent the ML Engineering team in technical discussions and communicate architectural decisions clearly to stakeholders.

What would ensure success in this role?💪

• Strong Python engineering background and experience with MLflow, Unity Catalog, Databricks, or equivalent platforms used for model lifecycle management.
• Proven experience designing ML infrastructure, including CI/CD, containerization with Docker or Kubernetes, and orchestration with Airflow or Prefect.
• Deep understanding of monitoring and observability frameworks such as Prometheus, Grafana, or Datadog, and a track record of improving pipeline reliability.
• Expertise in model governance, versioning, auditability, and operationalization from research to production.
• Solid knowledge of cloud infrastructure on AWS, GCP, or Azure, including cost effectiveness and security best practices.
• Experience leading cross functional initiatives and mentoring engineers.
• Ability to balance innovation and stability through structured experimentation, pilot phases, and safe adoption of new technologies.

What can you expect at Bondora? 

• Contribute to Bondora’s ambitious goal of reaching 1BN in revenue. Your skills and efforts will directly impact our growth trajectory and shape the future of our company.
• Our employees deserve the best. We recognize our people with a competitive salary and a generous benefits package (5 weeks of vacation, private healthcare compensation, hobby grant, mental healthcare support, share options and much more!)
• We provide an environment that encourages your personal and professional growth. As we constantly evolve and innovate, you’ll have endless opportunities (and budget) to expand your skills and skyrocket your career.

The next steps

If you have the guts, ideas, and a team vision, apply now! 

Our hiring process: 

1️⃣ Meet Kerli H., our recruiter, for an initial conversation about your background and ambitions.
2️⃣ Complete our personality and logic assessments via Alva Labs.
3️⃣ Meet Rafael, our Head of Data Science.
4️⃣ Complete case study.
5️⃣ Chat with Juris, our Chief Credit Officer.
6️⃣ If everything aligns, welcome to Bondora 🎉