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Metro backend title and mid-level seniority increase applicants, offset by niche LLM and agent expertise.
Java backend and cloud skills transfer well, but specialized LLM, MCP, and agent expertise require AI-focused background.
Multiple mandatory technical filters including Java, LLM experience, Kafka, AWS, and vector databases enforce strict shortlisting.
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Lead the adoption and integration of AI-assisted development practices, including designing LLM-powered workflows and AI agent project structures.
Develop and enhance the cloud-native Java backend logistics platform using Spring Boot, microservices, REST APIs, Apache Kafka, and PostgreSQL.
Prototype innovative LLM-based solutions and improve developer productivity through AI tool evaluation, training, and engineering guidelines.
6+ years professional experience with Java and Spring Boot.
Hands-on experience with AI-assisted software development using tools like OpenAI Codex or Claude Code.
Experience hosting or working with private LLMs on AWS; knowledge of Amazon Bedrock highly preferred.
Experience with Apache Kafka, microservices architecture, PostgreSQL database design and tuning, and AWS deployment (ECS/EKS, S3, API Gateway).
Strong backend engineering expertise combined with practical experience in integrating AI and LLM technologies within software development workflows.
Capacity to lead and mentor teams on AI-assisted coding best practices and productivity improvements.
Experience in scalable, cloud-native system design with emphasis on AI tooling within fast-paced logistics or similarly complex distributed environments.