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., Lang. Graph, 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