Java Full Stack Developer

Role: Java Full Stack Developer (AWS, Golang and AI skills)

Location: Ft. Lauderdale, FL/ Phoenix, AZ

Experience: Developer (5-7 years), Sr. Developer (8+ years)

Type: Fulltime permanent role with Infocepts

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)