Remote Java Tech Lead - AI-Driven Systems & Kafka

Quantiphi

United States

On-site

USD 150,000 - 210,000

Full time

40 hours ago
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Job summary

Quantiphi, an award-winning AI-first digital engineering company, seeks a Java Technical Lead (remote, USA) with 8+ years in Java/Spring Boot development and architecture. You will lead technical assessments, define system topology, and guide modernization efforts across Kafka and cloud workloads.

Work with Fortune 500 clients, collaborate with a high-energy team, and mentor engineers while shaping scalable solutions using Confluent Kafka, Spring Boot, and AWS-native services in a distributed,

Qualifications

  • 8+ years Java/Spring Boot development and architecture.
  • Production experience with Apache Kafka / Confluent Platform.
  • Amazon EKS, IRSA, Karpenter, managed node groups.
  • IBM MQ / Oracle AQ messaging systems knowledge.

Responsibilities

  • Lead comprehensive assessments across SYSIDs, evaluating architectures and integration points.
  • Document system inventories, identify technical debt, bottlenecks, and modernization opportunities.
  • Conduct stakeholder interviews and workshops to gather requirements and validate findings.
  • Define Confluent Kafka topic topology, partition strategy, and message ordering per business process.
  • Assess Spring Boot migration paths for Java engines and batch workloads.
  • Design Step Functions state machines for batch orchestration.
  • Create current-state and future-state diagrams.

Skills

Java/Spring Boot
System architecture
Stakeholder collaboration

Tools

Kafka/Confluent Platform
Amazon EKS/IRSA/Karpenter
IBM MQ / Oracle AQ

Job description

Quantiphi, an award-winning AI-first digital engineering company, seeks a Java Technical Lead (remote, USA) with 8+ years in Java/Spring Boot development and architecture. You will lead technical assessments, define system topology, and guide modernization efforts across Kafka and cloud workloads.

Work with Fortune 500 clients, collaborate with a high-energy team, and mentor engineers while shaping scalable solutions using Confluent Kafka, Spring Boot, and AWS-native services in a distributed,

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