Role Description You're early in your career – maybe just out of university, maybe a year or two in. You can code. You care about doing it well. And you want to work on something that actually runs in production, not just toy projects or internal dashboards nobody uses. At ShippyPro, we're looking for a Graduate / Junior Software Engineer to join our Tracking & Notifications team – the team that makes sure every shipment update reaches the right person at the right time, at scale. You'll work alongside experienced engineers who want to see you grow, not just get tickets done. Real ownership, real feedback, real growth. If you write clean code, ask sharp questions, and get genuinely curious when something breaks – keep reading. What You’ll Do - Contribute to the development and evolution of our tracking and notification services - Write, review, and ship code that runs at high volume in production - Work closely with our engineering team on design decisions, code reviews, and day-to-day problem solving - Collaborate with a distributed, international team across product, engineering, and operations - Get hands-on with microservices, event-driven systems, and cloud-native development on AWS - Use AI tools daily as part of our development workflow Qualifications - A strong foundation in software engineering fundamentals: data structures, algorithms, clean code, version control - Hands-on experience with databases (relational or NoSQL) you’ve written real queries and thought about data - Genuine curiosity: you don’t need to know everything, but you need to want to figure things out - Enthusiasm for working with AI – both as a dev tool and as part of what we build - Professional working proficiency in English (our team is international) Requirements - Nice to have – not blockers, but they’ll help you hit the ground running: - A degree in Computer Science or a related technical field - Experience with Python, TypeScript or PHP - Familiarity with cloud services or distributed systems from projects, internships, or personal work - Our stack – you don’t need to know all of this on day one, but this is the environment you’ll grow into: - Languages: Python and TypeScript (primary), PHP (also present) - Databases: PostgreSQL, Aurora, Redshift, DynamoDB - Infrastructure: AWS, Serverless Framework - Version control & CI/CD: Git, GitHub, GitHub Actions Benefits - Competitive salary between €28,000 and €35,000, calculated through our salary simulator – built on objective metrics, because we believe in unbiased compensation - Meal vouchers (office or remote) - Mental healthcare - Yearly learning budget and AI tools - Remote flexibility with expenses-paid trips to HQ for team meetups - No clock-in/out policy and one-time home office allowance - Career Growth Program – clear growth paths, structured goals, and continuous feedback - An international team that moves fast and cares about building things well Hiring Process - Application review - Intro call – 45-60 min with our People and Culture Team to align on expectations and context - Technical interview: a deep-dive with the engineering team on how you think and work - Final challenge: a short, practical coding exercise to see how you approach a real engineering problem A Note Before You Apply If you want to move on with the application, you’ll have to answer a few questions. Although we love AI (it’s part of almost everything we do!) we’d love to hear you. Be honest – no right or wrong answers here. Feel free to use AI if you want, but make sure your answers sound like you, not just a completed task. Thanks for considering joining our team. We look forward to hearing from you!

• Improving architecture across backend services and platform infrastructure, and defining long-term architectural strategy and technical standards across teams • Establish engineering standards that improve consistency, maintainability, reliability, and operational readiness • Scale distributed systems and improve performance across core services • Improve production engineering practices, including observability, testing, incident response, and post-incident review • Identify and reduce high-impact technical debt • Improve developer tooling, workflows, and engineering productivity • Help teams use agentic development tools effectively across planning, implementation, testing, review, and validation • Partnering with product and infrastructure teams on scalable, resilient systems and subsequently simplifying systems and reducing organizational complexity as the platform scales • Mentor Senior and Staff engineers through architecture reviews, technical coaching, and project guidance • Serve as a trusted technical advisor for difficult engineering and architectural decisions

• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs

• Own the end-to-end voice AI architecture — from Twilio media streams through LLM orchestration to TTS output and call disposition. • Design and implement multi-agent systems using tool calling, agent handoffs, and shared conversation state for complex patient workflows. • Build and optimize real-time audio pipelines — WebSocket streaming, codec handling (mulaw/PCM), VAD configuration, and interruption management. • Architect analytics and observability infrastructure for voice-specific metrics: per-segment latency (STT/LLM/TTS), call efficacy, disposition accuracy, and ASR error rates. • Solve voice-specific challenges: turn-taking timing, silence detection thresholds, barge-in recovery, medical term recognition, and end-to-end latency optimization. • Integrate voice agents with internal services via secure authenticated APIs. • Drive platform reliability — eliminate single points of failure, implement multi-provider LLM failover, and design graceful degradation paths. • Collaborate with product and clinical operations to improve self-serve efficacy rates and reduce call escalations. • Mentor team members on voice AI best practices and contribute to architectural decisions.