Senior Backend Engineer, Staffbase

• 6+ years of professional experience in backend software development
• Strong proficiency in Java/Kotlin
• Proven experience integrating various AI/ML models into production backend systems
• Practical experience with prompt engineering
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes)

Desirable

• Join our dedicated, fast-paced experimentation and innovation unit, where you'll leverage cutting-edge AI and LLM technologies
• This is an exciting opportunity to develop solutions that genuinely empower communicators and support frontline workers, driving strategic impact and exploring the full potential of new technologies
• Working with skilled and similar-minded professionals in a team that values diversity and inclusivity
• We aim to create a flexible and agile work environment that promotes the well-being and work-life balance of our employees
• We believe that team events during working hours play a vital role in building an exceptionally effective team, and we encourage them
• We are enthusiastic about technology and committed to using it to improve the world
• We follow the "You build it, you run it" approach and take pride in it
• Design, develop, and maintain scalable and fault-tolerant backend services that power our AI applications
• Apply advanced prompt engineering techniques to optimize model performance, manage context windows, and ensure reliable, high-quality responses
• Implement model integration patterns to connect and orchestrate various external and internal services
• Develop Agent-to-Agent (A2A) protocol communication strategies for complex multi-agent architectures
• Implement systems for Managing Conversational Protocols (MCP servers) and Agent-to-Agent (A2A) protocol to handle and maintain long-running, stateful interactions
• Define and implement observability standards for AI applications, including metrics for latency, cost, token usage, drift, and user-perceived quality
• Implement logging, tracing, and monitoring tools to quickly diagnose and troubleshoot issues in the end-to-end AI pipeline
• Collaborate with ML Scientists and Data Scientists to transition prototypes and models into production-ready, high-availability services
• Ensure the security, reliability, and performance of all production systems
• Participate in code reviews, architectural discussions, and technical strategy planning
• Mentor junior engineers and champion best practices in backend development and MLOps