Senior Backend Engineer – Integrations & Event Orchestration

You are an experienced backend engineer who thrives on making complex, interconnected systems reliable and maintainable. With at least 7 years of backend engineering experience and a strong track record in system integrations, you understand that successful platforms depend on more than individual services. They require dependable orchestration, consistent data, clear interfaces, and well-defined failure handling.

You combine strong Python skills with hands-on experience in event-driven or job-orchestration systems. You are comfortable designing integrations, investigating synchronization failures, optimizing database interactions, and taking ownership of services from design through production. You approach existing systems pragmatically, preferring evidence-based, incremental improvements over unnecessary rewrites.

You are ready to work as a technical peer to our lead engineer, owning the event orchestration engine and integrations that connect our Operations Project Management platform to the wider business ecosystem. You contribute to shared architectural decisions, establish testing practices, and help other engineers apply them.

You also bring practical experience with agent-based AI development workflows beyond code completion. You can work with specialized agents, maintain their instructions and skills, and connect them to development tools while retaining human accountability for decisions and quality. You communicate clearly, welcome technical debate, and support the team’s agreed direction once a decision is made.

Responsibilities:

• Owning and evolving the event orchestration service, including scheduled jobs, chained events, retries, and variable extraction, with a focus on reliability, observability, and maintainability.
• Designing and delivering integrations with internal and third-party systems through REST APIs, databases, and data warehouses, incorporating idempotent synchronization, failure handling, and reconciliation.
• Defining platform patterns alongside the lead engineer for API design, caching, authentication and authorization, and service-to-service communication, and documenting decisions through Architecture Decision Records.
• Establishing testing patterns across services, including unit, integration, and contract tests, mocking of external systems, and coverage gates in CI, while supporting adoption by service owners.
• Working within and improving an AI-agent development workflow spanning requirements analysis, development, testing, merge request review, and ticket management, with defined quality gates.
• Keeping the agents, instructions, skills, and knowledge base for your areas accurate and aligned with platform changes.
• Acting as the primary technical reviewer for your areas and mentoring less experienced engineers, particularly in integration design and implementation.
• Managing production health, performance, and incident follow-up for your services within a Kubernetes-based environment.

Requirements:

• Degree or Master in Informatic Engineering or related.
• At least 7 years of backend engineering experience, with a strong track record in system integrations, including APIs, ETL and synchronization pipelines, and data consistency across systems.
• Hands-on experience with event-driven or job-orchestration systems, including schedulers, workflow engines, queues, retries, and their failure modes.
• Strong Python development skills.
• Good knowledge of relational databases, such as MySQL, and SQL, including data modeling, query performance, and database migrations.
• Experience designing REST APIs, caching strategies, and authentication and authorization mechanisms, including OAuth2, tokens, and service accounts.
• Hands-on experience with agent-based AI development workflows beyond code completion, using role-based agents in tools such as GitHub Copilot, Claude Code, or similar.
• Experience writing or maintaining agent instructions and skills, and connecting agents to tools through MCP or similar mechanisms.
• A disciplined approach to AI configuration, including version control, review, ongoing maintenance, and recognition of where human validation is required.
• Demonstrated experience introducing or improving team testing practices, rather than solely writing tests.
• Practical experience with containers, Kubernetes, and GitLab CI or comparable CI/CD tooling.

Preferred experience:

• Django and Django REST Framework.
• Snowflake, Microsoft Fabric, or other cloud data platforms.
• Integrations with enterprise tools such as Jira, SharePoint/Microsoft Graph, or project portfolio management systems.
• Using MCP servers to connect AI agents to issue tracking, documentation, source control, and the wider development ecosystem.
• GitOps practices and tooling, such as FluxCD or ArgoCD, and secrets management.
• Experience as a technical lead or architect within a small engineering team.