Sr Full Stack Java Developer

Design and build responsive, accessible, and performant user interfaces using React

Deliver end-to-end features across UI, API, and data layers, ensuring consistency in design, performance, and security

Develop and maintain automated UI and end-to-end test suites using Playwright or equivalent

Design, develop, test, and deploy high-quality software solutions using Java and Spring Boot

Build scalable, high-performing RESTful APIs and microservices aligned with privacy and compliance requirements

Implement and support event-driven and message-based architectures using Kafka or similar technologies

Build scalable ETL frameworks using object-oriented Python and Java programming languages

Collaborate with cross-functional teams, including product, architecture, data, and privacy, to deliver compliant solutions

Contribute to system and application architecture, including service design, data flows, and integration patterns

Participate in code reviews, agile ceremonies, and technical design discussions

Troubleshoot and resolve complex software issues across development and production environments

Develop and maintain CI/CD pipelines, automation, and deployment workflows

Write and maintain clear technical documentation, including design documents and system specifications

Continuously evaluate and adopt modern technologies to improve system performance, reliability, and maintainability

Daily use of AI productivity tools (Claude, Cursor) is required across the software development lifecycle —including design, API and microservice development, code generation, code review, testing, debugging, deployment, documentation, and production support.

Design, build, and operate AI agents that automate software engineering tasks such as generating boilerplate code for new microservices, creating unit and API tests, analyzing logs, triaging incidents, and supporting CI/CD pipelines.

Build and integrate AI-enabled capabilities into backend services and APIs using foundation models, prompt engineering, and retrieval-augmented generation (RAG) patterns.

Implement audit logging, observability, and human-in-the-loop controls for AI agents and AI-assisted workflows running in Tier-0 production environments.

What You’ll Bring:

Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience

6+ years of software engineering experience, building and supporting enterprise-grade applications

Strong experience working in Agile or Scrum-based development environments

Demonstrated ability to work independently on complex technical problems while collaborating across teams

Strong analytical, problem-solving, and communication skills

Demonstrated experience building production user interfaces with React

Familiarity with foundation models, prompt engineering, retrieval-augmented generation (RAG), and AI agent development applied to full-stack application development, including enterprise reusable solutions

Must Have Skills:

Strong experience with JavaScript/TypeScript and React for building production user interfaces

Proficiency with messaging and event-driven systems such as Kafka

Experience with frontend build tooling, package management, and component-based design

Experience with end-to-end and UI test automation using Playwright or equivalent

Proficiency with front-end technologies, including HTML, CSS, JavaScript, and Webpack

Strong experience with Python object-oriented programming, Java, and Spring Boot

Experience building scalable REST APIs and microservices

Experience working with JSON and XML, including schema validation

Experience with Git, GitLab, and CI/CD automation

Hands-on experience working on Unix OS and proficient in shell scripting

Experience developing test automation using tools such as JUnit or Karate

Proficiency with API testing tools such as Postman

Experience working with relational databases and writing complex SQL

Experience with containerization and orchestration tools such as Docker and Kubernetes

Strong experience using observability and telemetry tools such as Splunk, AppDynamics, or Grafana

Hands-on experience with AI productivity tools (Claude and Cursor or similar IDE) and working knowledge of foundation models, prompt engineering, retrieval-augmented generation (RAG), and AI agent development.

Nice to Have:

Experience with Snowflake or cloud-based data platforms

Network Domain experience

Experience working in cloud-native environments (Azure, AWS, or GCP)

Experience contributing to system architecture or platform-level design decisions