About the role

Design and develop core services for an enterprise notifications platform using Java and cloud-native technologies. Implement and productionize AI/GenAI capabilities including RAG pipelines and LLM integrations to enhance communication features.

What they look for

Java Spring Boot AI/GenAI AWS Apache Camel Microservices LLM Integration RAG Pipelines Prompt Engineering Event-Driven Architecture REST APIs Vector Search CI/CD Dynatrace ELK Stack Agile

Requirements

Requires a bachelor's degree and over 8 years of experience in Java backend development and SDLC. Must have hands-on production experience with AWS and AI/GenAI implementation.

Full description

Job Title: Senior Java Developer with AI Experience

Location: Chicago, Illinois (Hybrid – 3 days/week onsite, locals only)

Company Overview

Glint Tech Solutions is a women-owned global IT staffing and recruiting firm serving clients across the USA and Canada. We connect top-tier technical talent with leading enterprise organizations.

Project Description

Our client, a leading enterprise organization, is seeking a Senior Java Developer with hands-on AI/GenAI experience to join its Digital Technology team supporting the enterprise Notifications platform. This is a hands-on senior individual contributor role focused on designing, developing, and modernizing notification platform services, event-driven integrations, and AI-enabled communication capabilities. This is not a management role — the expectation is active coding, debugging, and production delivery.

Key Responsibilities

Design and implement core services for the enterprise Notifications platform, including APIs, event-driven integrations, and orchestration components

Write, review, debug, and optimize production code hands-on

Build cloud-native backend services using Java, Spring Boot, Apache Camel, microservices, and AWS

Develop and integrate AI/GenAI capabilities including prompt design, LLM integration, RAG pipelines, embeddings/vector search, semantic search, classification, and summarization

Prototype, validate, and productionize AI features, factoring in latency, accuracy, cost, and reliability

Design for high availability, scalability, resiliency, observability, and security

Support integrations with internal systems, eventing platforms, and vendor-managed services

Troubleshoot complex production issues including performance and integration failures

Collaborate with architects, product owners, and stakeholders to convert requirements into working solutions

Contribute to technical design, code reviews, automated testing, and CI/CD practices

Mentor developers through code-level guidance while remaining primarily hands-on

Mandatory Skills

Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience

8+ years overall software engineering and SDLC delivery experience

8+ years hands-on Java backend development (Spring Boot, REST APIs, microservices)

3+ years hands-on experience with event-driven systems, messaging, or notification platforms

Hands-on experience with Apache Camel or equivalent integration frameworks

4+ years hands-on AWS experience (EC2, S3, RDS, VPC, CloudFront, Lambda, EKS, ECS, API Gateway, DynamoDB, DocumentDB, AmazonMQ)

Strong hands-on AI/GenAI implementation experience in production-grade applications

Practical experience with LLM integration, prompt engineering, RAG, embeddings/vector search, semantic search, classification, summarization, or AI-assisted workflow automation

Understanding of responsible AI and secure AI practices — data privacy, guardrails, evaluation, monitoring, auditability

Experience with observability tools (Dynatrace, ELK Stack, CloudWatch)

Experience in agile delivery environments with CI/CD, automated testing, and production support

Strong analytical and independent problem-solving skills

Effective communication with technical and non-technical stakeholders

Nice-to-Have Skills

Experience designing enterprise notification, communication, or eventing platform solutions

Experience with Twilio or similar communication/messaging platforms

Applying AI to communication use cases (personalization, routing, prioritization, intent classification, anomaly detection)

AI observability, LLMOps/MLOps practices, model/prompt evaluation

AWS certification or equivalent

High-scale, 24x7 production environment experience

Airline, travel, customer platforms, or crew operations domain experience