Senior Software Engineer - AI Platform & Frameworks
RemoteHungary or North Macedonia
Job Summary
Senior Software Engineer responsible for shaping and leading the platform that internal teams build on top of. Own the design of shared libraries, Spring Boot starters, and templates, making architecture, API, and trade-off decisions to enable easy onboarding of internal teams. Define patterns for agentic frameworks, orchestration, tool use, memory, and plumbing, and mentor teams in Python-based AI agent development using LangChain and LangGraph. Lead evaluation and guardrail strategy to measure agent quality and reliability. Drive Kotlin/Spring Boot platform work and client libraries, map the wider ecosystem, and multiply engineering impact by guiding adoption, documentation, and best practices. Set research direction, prototype promising approaches, and deliver production-ready foundations. Elevate developer experience with clear APIs, good defaults, useful errors, and documentation. Passion for agentic AI and capability to become a go-to expert for the organization.
Required Qualifications
- 7+ years of professional software engineering experience
- Deep experience with Kotlin / JVM and Spring Boot
- Strong instincts for API and library design
- Demonstrated technical leadership
- Genuine drive to lead on agentic AI and related tooling
- Excellent communication and self-sufficient in gathering context
- Pragmatism about Python with ability to ramp up quickly across Kotlin and Python stacks
Desired Qualifications
- Strong distributed systems background like messaging/queues (SQS, Redis), gRPC, event-driven architectures, including the failure modes and operational realities.
- Cloud experience (AWS preferred) and infrastructure-as-code.
- Experience growing a platform/DevEx practice by establishing standards, golden paths, and adoption across multiple teams.
- Contributions to or maintenance of open-source libraries or frameworks.
- Hands-on experience with LLMs, LangChain/LangGraph, or other agent frameworks.
- Experience defining evaluation / experiment-tracking / observability strategy for ML or agent systems (e.g. Langfuse, MLflow, or similar).
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