AI Engineer
HybridZagreb, Zagreb, Croatia
Job Summary
Design and develop serverless Python services integrating LLMs, vector databases, and graph knowledge graphs. Build and optimize multi-agent AI systems for reasoning, tool use, and workflow coordination. Implement RAG pipelines, data models, and retrieval strategies using hybrid search approaches. Deploy, scale, and monitor AWS infrastructure including Lambda, ECS, S3, and Step Functions. Integrate external APIs from OpenAI, Anthropic, Bedrock, and Hugging Face. Contribute to MLOps pipelines, process automation, and infrastructure improvements. Work on diverse projects across NLP, semantic search, and document automation. Collaborate with cross-functional teams to deliver scalable features. Stay current with advancements in AI, cloud infrastructure, and production-grade ML systems.
Required Qualifications
- Strong programming skills in Python
- Solid software engineering fundamentals, including OOP principles, clean code, and maintainable architecture
- Hands-on experience building production-ready AI-powered applications using LLMs, including chatbots, intelligent assistants, document automation, semantic search, summarization, classification, and information extraction workflows
- Practical experience designing and implementing RAG systems, including document ingestion, chunking strategies, embeddings, hybrid search, reranking, context construction, grounding, evaluation, and monitoring
- Strong practical knowledge of vector databases, graph databases, and knowledge graph concepts, including technologies such as Pinecone, OpenSearch Vector Engine, Neo4j, and Amazon Neptune
- Hands-on experience with multi-agent AI systems, including agent orchestration, function calling, memory management, task planning, workflow coordination, and integration with external systems
- More than 2 years of hands-on experience with AWS, including practical knowledge of services such as Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, RDS/Aurora, SQS/SNS, EventBridge, Step Functions, CloudWatch, IAM, Bedrock, or SageMaker
- Knowledge of MLOps, serverless architectures, Docker, CI/CD pipelines, model deployment, evaluation workflows, data pipelines, monitoring, and observability
- Familiarity with the full web stack, including RESTful APIs, WebSockets, authentication, authorization, backend performance optimization, and secure API integrations
- Strong analytical mindset, problem-solving skills, attention to detail, and a quality-focused engineering approach
- Excellent collaboration and communication abilities, with excellent written and spoken English
- Degree in Computer Science, Mathematics, Statistics, Engineering, or a relevant field, or equivalent practical experience
- Eligibility to work in Croatia
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