Java Full Stack Developer

Essential functions

• 5–10 years backend/platform engineering with strong, recent hands-on in Java/Spring Boot.

• Designed, built, and scaled RESTful APIs in production; API versioning, schema evolution, and backward compatibility.

• Data depth across MySQL/PostgreSQL and MongoDB/Cassandra; indexing, optimization, and caching patterns.

• Implemented RBAC, OAuth2/OIDC, JWT in real-world systems.

• Proficient with Git workflows (trunk-based or GitFlow), code reviews, and branching strategies.

• Testing: unit, integration, contract (e.g., Pact), and performance tooling; API tooling with Swagger/OpenAPI and Postman.

• Production-grade Docker and Kubernetes experience (deployments, services, ingress, HPA, rollout/rollback).

• Cloud proficiency on at least one of AWS/GCP/Azure (compute, networking, storage, IAM, managed DBs).

• AI Coding Tools and GenAI (new)

  • Daily-use proficiency with at least one AI coding tool in IDE/CLI; able to set team guardrails, policies, and best practices.

  • Hands-on experience integrating at least one LLM platform (e.g., Azure OpenAI, AWS Bedrock, Vertex AI, or OpenAI/Anthropic APIs) into backend services.

  • Practical prompt engineering and evaluation; experience with RAG using vector stores (e.g., OpenSearch, pgvector, Pinecone, Redis) and embeddings.

  • Familiarity with model lifecycle concerns: versioning, offline/online evaluation, A/B testing, telemetry, safety/abuse handling.

  • Comfort with “vibe coding”: collaborative AI-assisted workflows, rapid prototyping, live coding with AI agents, and converting exploratory prompts into production-grade code and tests.

• Clear communicator; able to ramp quickly and deliver independently with minimal supervision.

Qualifications

• Stack: Java, Spring Boot, REST APIs, MySQL/PostgreSQL and MongoDB/Cassandra, Docker/Kubernetes, Git, OAuth2/JWT, one cloud (AWS/GCP/Azure).

Would be a plus

• AI Coding Tools and GenAI (new)

  • Daily-use proficiency with at least one AI coding tool in IDE/CLI; able to set team guardrails, policies, and best practices.

  • Hands-on experience integrating at least one LLM platform (e.g., Azure OpenAI, AWS Bedrock, Vertex AI, or OpenAI/Anthropic APIs) into backend services.

  • Practical prompt engineering and evaluation; experience with RAG using vector stores (e.g., OpenSearch, pgvector, Pinecone, Redis) and embeddings.

  • Familiarity with model lifecycle concerns: versioning, offline/online evaluation, A/B testing, telemetry, safety/abuse handling.

  • Comfort with “vibe coding”: collaborative AI-assisted workflows, rapid prototyping, live coding with AI agents, and converting exploratory prompts into production-grade code and tests.

• Clear communicator; able to ramp quickly and deliver independently with minimal supervision.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.