Senior Backend Engineer

1w1 week ago

Elixirr Digital

Zagreb, HR · Full-time · €45,000 – €70,000

About this role

Elixirr Digital is transforming how consulting services are delivered. This role is critical to designing and implementing the backend infrastructure that powers AI-driven solutions and internal agent platform. Leverage modern cloud services like AWS and Azure, open-source frameworks, and latest AI developer tooling to build scalable, secure platform.

Move fast in a modern AI-assisted software development lifecycle. Help define how engineering org adopts AI tools responsibly, including harnesses, specs, evals, review practices and guardrails. Turn AI-generated code into production-grade software.

Work with advanced tools alongside a team of talented professionals. Design core backend architecture, drive microservices decisions, own services end-to-end. Integrate open-source frameworks and cloud services for high-availability solutions.

Operate fluently across AI developer stack, practice spec-driven development, maintain quality bar on AI code. Build internal guardrails and measure impact with engineering metrics. Hybrid opportunity from Rijeka or Zagreb locations.

Requirements

Experience with AWS services like EC2, S3, RDS, SQS, EventBridge
Experience with Azure services like Cosmos DB, Event Hub, AKS
Proficiency in open-source frameworks such as FastAPI, Django, Spring Boot, Node.js frameworks
Familiarity with agent platform integrations including LLM providers, vector stores, LangGraph, Semantic Kernel
Skills in containerization and serverless like AWS Lambda, Azure Functions, ECS
Expertise in security practices: fine-grained authorization, data protection
Ability to review AI-generated code for correctness, security, performance and maintainability

Responsibilities

Design, implement and maintain the core backend architecture for Elixirr’s AI-augmented consulting platform and agent platform
Drive decisions on microservices, containerization and serverless solutions based on performance, cost and scalability requirements
Own services end-to-end: architecture, implementation, testing, deployment, observability and on-call
Operate fluently across a modern, layered AI developer stack including editor-level copilots and AI in CI
Practice spec-driven, harness-based development with precise specifications and acceptance criteria
Build and maintain internal guardrails like eval harnesses, security checks and policy controls for AI-assisted development
Evaluate and integrate open-source frameworks to reduce build time and improve reliability
Implement robust security measures including OAuth 2.0, OIDC, JWT and secrets management