All active Cloud Architect roles based in Latvia.
Pick a job to read the details
Tap any role on the left — its description and apply link will open here.
Share this job
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
Scripting, Automation & DevOps
Data Pipeline Development
Cloud & Infrastructure
Required Qualifications / Skills
Preferred Skills (Highly Desired)
Data Engineering & Pipelines
Database & Caching Technologies
Infrastructure & Security
What We Offer
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.
Ready to apply?
Apply to Verifone
Share this job
Kimchi is the AI platform inside CAST AI. We started by helping companies run LLMs on their own Kubernetes clusters - now we're building the execution layer where agents do real work.
Our Infrastructure today: multi-model inference (MiniMax, Kimi, GLM-5, Nemotron, DeepSeek) with intelligent routing, an OpenAI-compatible API, and deployment flexibility from our GPUs to your VPC. The inference layer is the foundation. What we're hiring for sits on top of it: coding agents, agent runtimes, orchestration systems, and the reliability engineering that makes them actually finish things.
Tech Stack: TypeScript, Go, Kubernetes, AWS/GCP/Azure, MCP, Prometheus/Grafana/Loki, GitLab CI, ArgoCD.
Why harness engineering matters here
OpenAI and Anthropic ship models. They also ship one harness each - the scaffolding that turns a raw model into something that can plan, execute, recover, and complete work. We ship a different kind of harness: one built for cost-conscious, long-horizon autonomy, running on inference infrastructure we control end-to-end.
A decent model with a great harness beats a great model with a bad harness. We've watched this play out. The gap between what today's models can do and what you see them doing is largely a harness gap - and that gap is where we operate.
What you'll build
The ratchet.
Every time our agent makes a mistake, we engineer a solution so it never makes that mistake again. That means hooks that enforce constraints the model "knows" but forgets: pre-commit lint checks, permission gates, context compaction before the window fills. Success is silent, failures are verbose.
Long-horizon execution.
Our harness is built around spec-driven autonomy: meta-prompting, fresh context per task, worktree-per-slice git strategy, automatic replanning, crash recovery, stuck detection. We're implementing Ralph loops - when the model tries to exit, we intercept and reinject the goal into a fresh context. The agent reads state from disk and continues. Multi-session, multi-day work, without context rot.
Planner/executor splits.
Planning with a reasoning model, executing with a fast one, evaluating with a third. Separating generation from evaluation beats self-verification because agents reliably skew positive when grading their own work.
The harness surface.
CLI, TUI, MCP integration, sandboxed execution, telemetry. Our AGENTS.md is short - every line traces to a specific thing that went wrong. TypeScript on the surface, Go where it matters.
Memory and context.
Moving agents off laptops, giving them state that survives across sessions, managing context so information lands where it's actionable. Compaction, tool-call offloading, progressive skill disclosure.
What makes this different (with receipts)
You've seen the pitch: "we route to the best model." Everyone says that. Here's what we actually have:
What success looks like (after 6 months):
This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.
*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.
#LI-Remote
Ready to apply?
Apply to Cast AI
Cookies & analytics
This site uses cookies from third-party services to deliver its features and to analyze traffic.