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You will design, implement, and deploy a high-volume messaging platform from scratch while leveraging AI coding agents to accelerate development. You will be responsible for the end-to-end lifecycle of backend services, ensuring production readiness, scalability, and reliability.
Own meaningful functionality end to end - from understanding the problem and designing the solution to implementation, testing, deployment and production readiness.
Work across APIs, application services, PostgreSQL and asynchronous or event-driven processing.
Work with incomplete or evolving requirements and turn them into pragmatic technical solutions.
Use AI coding agents throughout the development workflow - for exploration, implementation, refactoring, testing, debugging and documentation.
Build observability, testing and failure handling into the solution instead of treating them as follow-up work.
Collaborate directly with other senior engineers, SREs and the architect on technical decisions and production behaviour.
Contribute to a modular architecture that allows several engineers and their AI tooling to work independently in parallel.
Support the platform through production readiness, migration and operation.
Experience with telecom, messaging, CPaaS or carrier platforms.
Knowledge of A2P/SMS concepts such as SMPP, routing, DLRs, CDRs, rating or wholesale messaging.
Strong backend engineering experience (min. 5 years of commercial experience). Java/Kotlin is our primary choice, but we are open to candidates who also know other languages.
Experience using AI across the full SDLC - from refining requirements and turning them into development plans, through architecture and implementation, to testing, code review and deployment.
Ability to orchestrate and supervise AI agents.
Proven ability to take ownership of a problem end to end rather than work only from narrowly specified tickets.
Comfort working with ambiguity and turning partial requirements, user needs and technical constraints into working software.
Ability to move quickly without treating speed as permission to lower engineering standards.
Professional English.
Experience with billing, payments, metering or another domain where transactional correctness directly affects money.
Experience building high-volume data pipelines and idempotent processing.
Experience with message brokers, asynchronous workflows or high-volume transaction processing.
Experience with Kubernetes-based production environments.
React/TypeScript experience so you can contribute across the full stack.
Experience building internal operations or back-office platforms.
Experience supporting systems during production incidents, migrations or cutovers.
Build something from scratch: you’ll work on a greenfield platform that will carry a real, revenue-generating telecom business.
Real engineering problems: high-volume processing, correctness, distributed systems and production reliability rather than incremental feature maintenance.
Agentic engineering for real: AI coding agents are part of the actual delivery model rather than an experiment or an optional productivity tool.
Small senior team: short decision paths, direct collaboration and little organisational distance between a problem and the person solving it.
End-to-end responsibility: what matters is not how much code gets generated, but whether the software actually works in production.
A specialised domain without an artificial entry barrier: telecom or A2P experience is valuable, but we are equally interested in strong engineers from adjacent high-volume and transaction-heavy systems.
Longer-term perspective: the platform moves from build through migration into production operation and further development.
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