Backend Engineer

• Build and optimise mission-critical microservices using Python, Django, and Django REST Framework (DRF)
• Implement robust unit testing with Pytest and automated quality checks
• Architect scalable APIs capable of handling high-concurrency traffic during peak travel seasons
• Identify and resolve performance bottlenecks, including N+1 query issues and asynchronous task optimisation
• Collaborate with Product and QA teams to translate complex business logic into maintainable technical solutions
• Champion software lifecycle best practices, including design patterns, documentation, and comprehensive code reviews

Senior Backend Engineer – Python, Django

• Develop software engineering products and services in the Product & Engineering team
• Contribute to Paddle’s payment infrastructure as a Merchant of Record for digital product companies
• Work in a digital-first environment remotely, from company hubs, or through a combination of both
• Collaborate within a transparent, collaborative, and respectful global team
• Engage with new challenges, learning opportunities, and internal and external training

Software Engineer – Go

• Own and maintain complex Airflow DAGs for pricing automation, margin reporting, and cost analysis
• Build and manage rate deck pipelines across multiple product lines
• Develop and maintain pricing APIs and services in Python with async programming
• Analyse CDR/MDR data to identify vendor discrepancies and drive refund and reconciliation workflows
• Build automated discrepancy resolution and self-healing pipelines
• Create and maintain financial reporting, including monthly margin reports, negative margin alerts, and GP calculations
• Design and build new automation for quoting workflows
• Own backend systems and pipelines supporting pricing, margin reporting, and cost analysis across Telnyx's product portfolio
• Collaborate with finance, sales, and product teams that rely on these services for pricing decisions, vendor-cost reconciliation, and business reporting

Software Engineer, Python

• Own the technical vision and architectural integrity of Fintua’s fintech platform across new and existing systems
• Own end-to-end solution architecture for new product initiatives and production systems
• Assess architectural debt, integration gaps, and duplicated capabilities; define and prioritise remediation roadmaps
• Design integration-ready, debt-conscious new solutions and define target-state architectures and migration paths
• Establish and enforce architectural guardrails and standards, including AI and agentic capability standards
• Build and maintain a platform-wide technical debt register and champion debt reduction
• Identify and eliminate redundant systems, data stores, and integration patterns
• Define definition-of-done standards covering testing, documentation, decoupling, and observability
• Design the integration layer for internal solutions and external parties
• Establish API-first integration patterns and own API strategy and governance
• Evaluate and onboard external integrations and partners for architectural and security fit
• Define the architecture and roadmap for a shared data lake/data platform
• Design data models, ingestion pipelines, access patterns, governance, lineage, access control, and privacy-by-design controls
• Drive migration from siloed or duplicated client data stores to the shared data layer
• Architect for high availability, fault tolerance, and low-latency transaction processing at scale
• Lead architectural reviews and set design standards across engineering teams
• Mentor senior and staff engineers and act as technical escalation point
• Maintain architecture documentation, decision records, technical debt registers, and system/data-flow diagrams
• Support due diligence, audits, and regulatory examinations
• Assess emerging fintech technology trends

Platform Architect

• Design, implement, test, and operate backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration
• Define and build a scalable multi-tenant SaaS architecture with tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries
• Build APIs and service interfaces for AI agents, MCP tools, CLIs, and internal applications to retrieve context, provenance, confidence signals, and warnings
• Partner across product and infrastructure to balance experimentation with long-term reliability
• Instrument services with metrics, logs, traces, alerts, and dashboards
• Use observability tools to understand system behavior and improve reliability
• Shape architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices
• Take ownership of innovative AI solutions, ensuring scalability, maintainability, and alignment with user workflows

Staff Backend Engineer – Grafana Second Horizon

• Design, implement, test, and operate backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration
• Define and build a scalable multi-tenant SaaS architecture with tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries
• Build APIs and service interfaces for AI agents, MCP tools, CLIs, and internal applications to retrieve context, provenance, confidence signals, and warnings
• Balance rapid experimentation with long-term reliability as the project moves from prototype to production
• Instrument services with metrics, logs, traces, alerts, and dashboards
• Shape architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices
• Take ownership of scalable, maintainable AI solutions aligned with real user workflows
• Collaborate across product, infrastructure, and engineering teams

Staff Backend Engineer – Grafana

• Design, implement, test, and operate backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration
• Define and build a scalable multi-tenant SaaS architecture with tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries
• Build APIs and service interfaces for AI agents, MCP tools, CLIs, and internal applications to retrieve context, provenance, confidence signals, and warnings
• Make practical tradeoffs between rapid experimentation and long-term reliability as the project moves from prototype to production
• Instrument services with metrics, logs, traces, alerts, and dashboards
• Use observability tools to understand system behavior and improve reliability
• Shape architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices
• Take ownership of AI solutions and ensure they are scalable, maintainable, and aligned with real user workflows
• Collaborate across product, infrastructure, and engineering teams

• Design, implement, test, and operate backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration
• Define and build a scalable multi-tenant SaaS architecture with tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries
• Build APIs and service interfaces for AI agents, MCP tools, CLIs, and internal applications to retrieve context, provenance, confidence signals, and warnings
• Partner across product and infrastructure to balance experimentation with long-term reliability
• Instrument services with metrics, logs, traces, alerts, and dashboards
• Use observability tools to understand system behavior and improve reliability
• Shape architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices
• Take ownership of AI solutions that are scalable, maintainable, and aligned with user workflows

• Design, implement, test, and operate backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration
• Define and build a scalable multi-tenant SaaS architecture with tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries
• Build APIs and service interfaces for AI agents, MCP tools, CLIs, and internal applications to retrieve context, provenance, confidence signals, and warnings
• Partner across product and infrastructure to balance experimentation with long-term reliability
• Instrument services with metrics, logs, traces, alerts, and dashboards
• Contribute to architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices
• Take ownership of AI solutions and ensure they are scalable, maintainable, and aligned with user workflows
• Collaborate asynchronously and across teams in a highly autonomous environment