Lead Java Developer

Position Java + AI Lead

Location Phoenix, AZ - 3 days a week (Hybrid)

Hire Type FTE

Skills Java + AI Lead

L3 — Senior FDE (5–8 years)

Attribute L3 — Senior FDE

5–8 yrs

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
• Java/Spring Boot, GitHub + Copilot, Maven, PostgreSQL, Docker, Jira/Confluence, GCP

Primary Tools & Stack 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