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

Akaasa Technologies
Chicago, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 167K

Job location

Chicago, United States of America

Tech stack

Java
Artificial Intelligence
Amazon Web Services (AWS)
Automation of Tests
Continuous Integration
Software Debugging
Monitoring of Systems
Enterprise Messaging Systems
Systems Development Life Cycle
Release Management
Search Technologies
Software Engineering
Twilio
Camel
Large Language Models
Prompt Engineering
Spring-boot
GIT
Event Driven Architecture
AI Platforms
Kubernetes
Integration Frameworks
Machine Learning Operations
Cloudwatch
REST
Dynatrace
Docker
ELK
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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