Role: Java Full Stack Developer/ Sr Developer

Role: Java Full Stack Developer/ Sr Developer with AWS, Golang and AI skills

Location: Phoenix, AZ or Ft. Lauderdale, FL

Years of Exp: Developer (5-7 years), Sr. Developer (8+ years)

Role Overview:

We are seeking a highly skilled Full Stack Developer with expertise in Java, AWS, Golang, and AI/ML

integration to build next-gen, intelligent, cloud-native applications. The role focuses on developing

scalable microservices, embedding AI capabilities into business workflows, and delivering high-

performance systems.

Key Responsibilities

·       Design and develop end-to-end solutions across frontend, backend, and AI layers

·  Build scalable microservices using Java (Spring Boot) and Golang for high-performance workloads

·       Develop modern UI using React/Angular

·       Design and deploy cloud-native applications on AWS

·       Integrate AI/ML models and APIs (LLMs, predictive models) into applications

·       Build and manage RESTful and event-driven architectures

·       Implement CI/CD pipelines and DevOps practices for cloud deployments

·       Ensure performance, scalability, and security of applications

·       Collaborate with data scientists, architects, and product teams

Required Skills & Qualification

·       5+ years of full stack development experience

·       Strong expertise in Java (5+), Spring Boot, Python, and Golang

·       Hands-on experience with AWS services: EC2, Lambda, S3, API Gateway, RDS, DynamoDB, SNS/SQS, IAM

·       Frontend experience with React/Angular, JavaScript, HTML, CSS

·       Experience integrating AI/ML services or APIs (OpenAI, AWS Bedrock, SageMaker, etc.)

·       Strong knowledge of microservices, REST APIs, and distributed systems

·       Experience with Docker, Kubernetes (EKS), and CI/CD tools

·       Familiarity and experiences with NoSQL databases like: PostgreSQL, Cassandra, Couchbase, Redis, Elasticsearch

Preferred Qualifications

·       Experience building AI-powered applications (chatbots, recommendation systems, NLP use

·       cases)

·       Knowledge of RAG architectures, prompt engineering, and LLM integration

·       Experience with streaming/event platforms (Kafka or AWS EventBridge)

·       Exposure to MLOps practices and ML lifecycle management

·       Understanding of security standards (OAuth2, JWT)