Java Developer, Cloud, Gen AI

Infotree Global Solutions

. Design, develop, test, deploy, and maintain high-quality, scalable, production-ready software .

Posted 10/19/2026full-timeWarsaw • PolandSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing scalable, cloud-native applications using Java, Spring Boot, and Kafka, while ensuring high-quality software delivery through best practices in engineering and technical leadership. Proficient in building event-driven architectures and integrating machine learning applications, with a strong focus on performance and operational reliability.

Highest-signal resume keywords

Java DevelopmentSpring Boot FrameworkApache KafkaKubernetes DeploymentEvent-Driven Architecture

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Software EngineeringREST API DevelopmentMicroservices ArchitectureContainerization with DockerPython ProgrammingCI/CD PipelinesAutomated TestingData Pipeline DevelopmentDistributed SystemsPerformance Optimization

Soft Skills

Problem-SolvingTechnical LeadershipCollaborationTask DecompositionOwnership

Tools & Technologies

KubernetesDockerApache SparkSnowflakeDatabricksGenerative AIMachine LearningGoogle ADKLangChainLangGraph

Industry Keywords

Cloud-Native ApplicationsDistributed ProcessingEvent-Driven ArchitecturesData QualityBatch ProcessingStreamingLLM-Powered ApplicationsVector DatabasesAgent WorkflowsLLM Evaluation

Tech Stack

Tools & technologies

ApacheCloudDistributed SystemsDockerJavaKafkaKubernetesMicroservicesPythonSparkSpringSpring BootSpringBoot

About the role

Key responsibilities & impact

Design, develop, test, deploy, and maintain high-quality, scalable, production-ready software
Build and maintain cloud-native applications and distributed systems using Java, Spring Boot, Kafka, Kubernetes, and Python
Design and implement reusable libraries, frameworks, and engineering components
Break down complex projects into technical tasks, identify dependencies, estimate effort, and support delivery planning
Contribute to technical design decisions, code reviews, engineering standards, and best practices
Develop resilient event-driven architectures and distributed applications
Improve application performance, scalability, security, observability, and operational reliability
Collaborate with cross-functional teams to deliver high-quality software
Contribute to data engineering and distributed processing solutions where required
Support development and integration of Generative AI and machine learning-based applications
Provide technical leadership as a senior individual contributor, including solution design, task decomposition, code quality, and engineering best practices

Requirements

What you’ll need

7+ years of professional software engineering experience
Strong hands-on experience with Java and Spring Boot
Experience developing REST APIs, microservices, and distributed applications
Practical experience with Apache Kafka and event-driven architectures
Experience deploying and operating containerized applications using Docker and Kubernetes
Working knowledge of Python and modern cloud-native technologies
Strong understanding of software engineering principles, design patterns, clean code, and automated testing
Experience with CI/CD pipelines, production troubleshooting, and application monitoring
Ability to break down complex technical requirements into actionable engineering tasks
Strong problem-solving skills and the ability to take ownership of technical deliverables
Formal people management experience is not a prerequisite
Preferred: 3+ years of experience building or maintaining large-scale data pipelines and distributed processing systems
Preferred: Experience with Apache Spark, Snowflake, and Databricks
Preferred: Understanding of batch processing, streaming, data quality, and pipeline performance optimization
Preferred: 3+ years of experience or relevant hands-on exposure to GenAI or ML-based applications
Preferred: Experience with LLM-powered applications and integration of LLM APIs
Preferred: Familiarity with Google ADK, LangChain, and LangGraph
Preferred: Understanding of RAG, embeddings, vector databases, agent workflows, and LLM evaluation