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Java FSD (Angular) + AI Lead

OrbITpeopleAZ🇺🇸United StatesPosted 2 Sept 2026

Why This Role Stands Out

This hybrid role offers you the chance to lead critical software development initiatives, integrating cutting-edge AI technologies into impactful client solutions. You'll thrive if you're a seasoned Java Full Stack engineer with a passion for technical leadership and shaping architectural decisions. Apply to elevate your career and contribute to innovative projects.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
AZ, United States
Posted
1 week ago
DockerMicroservicesSpringSpring BootAPI GatewaySonarQubeAngularConcreteConfluenceGoogle CloudJavaJiraKafkaLLMPostgreSQLRESTRedisTerraform

Job Description

Forward Deployed Engineer - Java Full Stack (Angular) + AI Lead
L3 - Senior FDE (5 8 years)

Mission / Role Summary

Owns an entire mid-size engagement or leads a major workstream on a strategic program (e.g., a workflow-modernization (Pega Camunda) or data-modernization domain). Technical face of Persistent to the client at module level.
Key Responsibilities
  • Lead design and delivery of a program module; set code standards and module architecture
  • Scope new workstreams; translate vague executive asks into concrete engineering plans
  • Drive AIDLC adoption and measure Copilot / Speckit ROI on the module
  • Lead design and PR reviews; mentor L1/L2 FDEs
  • Own the client technical relationship at workstream/module level
Engineering Skills (Core)
  • 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)
AIDLC & GenAI Capability
  • 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
Primary Tools & Stack
  • 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).
Client / Stakeholder Engagement
Trusted technical advisor at module level; runs client design reviews and demos.
Behavioral & Leadership Expectations
General, Behavioral & Problem Solving Project explanation, Recent work, Technical challenges, Code reviews, Problem solving skills)
Technical leadership and accountability for outcomes
Mentoring and firm contribution (playbooks, reusable assets)

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