Java AI Platform Engineer- Notifications Platform (Java, AWS, GenAI)

Akaasa Technologies
Chicago, IL, United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$105,000.0 - $167,000.0
Working hours
Regular working hours

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Automation of Tests Continuous Integration Software Debugging Monitoring of Systems Enterprise Messaging Systems Systems Development Life Cycle Release Management Search Technologies Software Engineering
+17 more
Twilio Apache Camel Large Language Models Prompt Engineering Spring-boot Git Event Driven Architecture AI Platforms Kubernetes Integration Frameworks Machine Learning Operations Cloudwatch Restful APIs Dynatrace Docker Elk Stack Microservices

Job description

This is a hands-on Individual Contributor (IC) role focused on designing, developing, modernizing, and supporting enterprise-scale notification services and AI-enabled communication platforms used across customer and crew applications.The ideal candidate will be an experienced Java Backend Engineer with strong AWS Cloud, Microservices, and AI Engineering expertise, including LLM integration, RAG pipelines, vector databases, tool calling, and cloud-native deployments. This role requires someone who spends the majority of their time coding, debugging, designing, and delivering production-ready software.

Requirements

  • 8+ years of software engineering experience.
  • 8+ years of hands-on Java backend development.
  • Strong experience with:

  • Spring Boot
  • REST APIs
  • Microservices
  • 4+ years of AWS cloud development.
  • 3+ years working with event-driven architectures and messaging systems.
  • Experience with Apache Camel or similar integration frameworks.
  • Strong production experience implementing AI/GenAI solutions including:

  • LLM integration
  • Prompt Engineering
  • RAG
  • Embeddings
  • Vector Search
  • Semantic Search
  • AI Workflow Automation
  • Experience with Docker, Kubernetes, and CI/CD.
  • Knowledge of secure AI engineering, AI guardrails, data privacy, and AI governance.
  • Experience with monitoring tools such as Dynatrace, ELK Stack, or CloudWatch.
  • Strong understanding of SDLC, Git, automated testing, release management, and production support.

Others:

  • Experience with enterprise notification or messaging platforms.
  • Twilio or similar communication platform experience.
  • AI-powered personalization and content generation.
  • AI observability, LLMOps, or MLOps.
  • AWS Certification.

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