Java Developer with AI Exp - Remote (Offshore)

Overview

Remote
Depends on Experience
Full Time
Able to Provide Sponsorship

Skills

Backend microservices using Python
Java
Springboot
APIs
REST
GraphQL
CI/CD
NLP
AI

Job Details

Role: Java Developer with AI
Location: Offshore Remote
NOTE: Only Resumes from offshore.

Job Description:

Responsibilities
Develop and maintain Backend microservices using Python, Java and Spring Boot
Build and integrate APIs (both GraphQL and REST) for scalable service communication
Deploy and manage services on Google Cloud Platform (GKE)
Work with Google Cloud Spanner (Postgres dialect) and pub/sub tools like Confluent Kafka (or similar)
Automate CI/CD pipelines using GitHub Actions and Argo CD
Design and implement AI-driven microservices
Collaborate with Data Scientists and MLOps teams to integrate ML Models
Implement NLP pipelines
Enable continuous learning and model retraining workflows using Vertex AI or Kubeflow on Google Cloud Platform
Enable observability and reliability of AI decisions by logging model predictions, confidence scores and fallbacks into data lakes or monitoring tools

Required Qualifications
5+ years of backend development experience with Java and Spring Boot
2+ years working with APIs (GraphQL and REST) in microservices architectures
2+ years experience integrating or consuming ML/AI models in production environments (e.g. RESTful ML APIs, TensorFlow Serving or Vertex AI Endpoints)
Experience working with structured and unstructured data (e.g. Rx Claim metadata, clinical documents, NLP processing).
Familiarity with ML model lifecycle - from data ingestion, training, deployment, to real-time inference (MLOPS)
2+ years hands-on experience with Google Cloud Platform, AWS, or Azure
2+ years working with pub/sub tools like Kafka or similar
2+ years experience with databases (Postgres or similar)
2+ years experience with CI/CD tools (GitHub Actions, Jenkins, Argo CD, or similar)
Preferred Qualifications
Hands-on experience with Google Cloud Platform
Familiarity with Kubernetes concepts; experience deploying services on GKE is a plus
Strong understanding of microservice best practices and distributed systems
Familiarity with Vertex AI, Kubeflow or similar AI platforms on Google Cloud Platform for model training and serving
Understanding of GenAI use cases, LLM prompt engineering and agentic orchestration (e.g. LangChain, transformers)
Experience deploying Python-based ML Services into Java microservice ecosystems (via REST, gRPC or sidecar patterns)
Knowledge of claim adjudication, Rx domain logic or healthcare specific workflow automation

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.