Lead Java Developer (Python + AI)
We are building a SWAT-style Forward Deployed Engineering (FDE) team to tackle critical technical challenges across Enterprise Platforms and pioneer AI-assisted software delivery at scale. We are seeking hands-on, high-impact engineers who can rapidly onboard onto unfamiliar systems, deliver end-to-end solutions, and leverage modern AI tooling under tight timelines and high ambiguity.
Req.#1072181532
Responsibilities
- Rapid Onboarding & Delivery: Quickly onboard onto unfamiliar codebases, build and run applications locally, and deliver working solutions within tight deadlines
- Production Troubleshooting: Diagnose and resolve complex production issues across multiple platform teams, working across distributed systems and microservices architectures
- End-to-End Ownership: Own feature delivery from requirement understanding and code development to integration testing, CI/CD pipeline integration, and implementation
- AI-Assisted Development: Use advanced AI tools (e.g., Copilot, Claude Code) to generate code, create test cases, accelerate debugging, and critically evaluate outputs for correctness
- Agent & Workflow Innovation: Develop agents, dynamic workflows, and agent orchestration tools while configuring and improving build pipelines (Gradle/Maven, CI)
- Cross-Team Collaboration: Collaborate with platform teams to resolve incidents, prevent recurrence, and—in the lead role—coordinate SWAT engagements
Requirements
- Enterprise Experience: Strong background working with enterprise-scale distributed systems and microservices architectures
- Core Technical Stack: Proficiency in Java, Python, Spring Boot, APIs, and Go (Golang)
- AI & Tooling Fluency: Practical experience with structured prompt writing, multi-step AI workflows, validation of AI-generated code, and agent-based tools (e.g., LangGraph, Claude Code)
- Independent Execution: Proven ability to take a system independently through clone, build, debug, modify, test, and CI/CD integration
- Build & CI/CD Mastery: Hands-on experience with build tooling (Gradle/Maven), environment/dependency management, and CI/CD pipelines (e.g., GitHub Actions)
- Debugging & Resilience: Strong root cause analysis skills for build failures, dependency conflicts, and runtime issues in high-pressure environments
