Senior Java Developer

Essential functions

• Delivery and ownership
  Translate epics into actionable technical tasks; own end-to-end design, implementation, testing, and production rollout.
  Produce high-quality code, reviews, and technical docs; unblock the team and resolve complex defects/perf issues.

• Architecture and APIs
  Design/implement RESTful services with versioning, backward compatibility, and API-first standards (OpenAPI/Swagger).
  Apply resilient patterns (retries, circuit breakers, idempotency) and data caching where appropriate.

• Data and performance
  Model schemas for relational and NoSQL stores; tune indexes/queries; guide sharding/partitioning and read/write strategies.

• Security
  Implement RBAC, OAuth2/OIDC, JWT, secret management; adhere to secure coding and threat-mitigation practices.

• Cloud and DevOps
  Containerize with Docker; deploy/operate on Kubernetes (deployments, services, ingress, HPA).
  Contribute to CI/CD and IaC (e.g., GitHub Actions/Jenkins; Terraform/CloudFormation); enable blue/green or canary releases.

• Quality and observability
  Establish test strategy across unit/integration/contract/performance; instrument logs/metrics/traces; define SLOs and runbooks.

• Collaboration
  Partner with Product and adjacent teams on scope/risk/estimates; communicate trade-offs and status crisply.

• GenAI and AI Coding Tools (new)
  Lead adoption of AI coding tools (e.g., GitHub Copilot, Cline, Aider) to accelerate delivery while enforcing code quality, review, and security gates.
  Design and integrate GenAI capabilities into services (e.g., retrieval-augmented generation, summarization, classification, code-gen pipelines).
  Establish prompt patterns, reusable prompt libraries, and evaluation harnesses for LLM features; define metrics (accuracy, latency, safety).
  Implement responsible AI practices: PII redaction, prompt/response logging, guardrails, usage policies, model/version governance.
  Optimize inference performance and cost (model selection, context-window strategy, caching, batching, streaming).
  Champion “vibe coding” practices: collaborative, conversational development with AI agents and peers (live prompting, rapid prototyping, pair-programming with AI, iterative test generation).

Qualifications

• 8–12 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.

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.