Hi
Our client is looking for a Forward Deployed Engineer project in Phoenix, AZ below is the detailed requirement.
Job positing Title: Forward Deployed Engineer
Location: phoenix, AZ
Required Skills: java full stack with angular experience , AI
Job description:
• Bachelor’s degree in related field
• Java/Spring Boot, GitHub + Copilot, Maven, PostgreSQL, Docker, Jira/Confluence, Google Cloud Platform fundamentals.
• Harness, GKE/Cloud Run, Kafka, SonarQube, Vertex AI basics; IBM Watsonx for Z (Track 3).
• Terraform, Camunda/Appian, Vertex AI, agentic frameworks (Agents + Skills, MCP).
• Java versions 8, 11, 17, 21, SOLID principles, OOP concepts, Design patterns, Functional interfaces Java migration patterns
• Spring Framework – Core Concepts - Dependency Injection, MVC architecture, Controller responsibilities, Transaction management, Core Spring annotations)
• Spring Boot - (Spring Boot features, Core annotations, Dependency Injection, Application context, @SpringBootTest, Global exception handling, Configuration management, Multi-environment setup, ORM best practices, Security basics, Multiple DB connections, Version upgrades)
• Microservices Architecture (Monolith to microservices principles, Microservice patterns, Saga pattern, Orchestration vs Choreography, API Gateway, Distributed data consistency, Failure handling, Resilience strategies)REST APIs & Integration (REST lifecycle,
• Spring REST annotations, External API calls, Timeout & fallback handling, API performance troubleshooting)Caching & Performance Optimization (Redis caching, @Cacheable, Cache eviction strategies, Performance tuning)
• Security (Authentication & Authorization, Spring Security basics, Secure configuration management, Certificates & credentials handling)
• Understands the AIDLC stages and where AI accelerates the SDLC
• LLM application basics: prompting, RAG concept, tool/function calling
• Effective day-to-day use of GitHub Copilot; writes simple eval cases
• Solid LLM application patterns — RAG, tool/function calling, MCP basics
• Spec-driven development; prompt and context-engineering fundamentals
• Designs RAG and agentic solutions; advanced context engineering
• MCP integrations across enterprise tools; defines eval strategy
• Drives measurable developer-productivity outcomes from AI tooling
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