Lead Software Engineer

Position Requirements

YOU ARE Fluent with AI-assisted development you use spec-driven tools like Kiro AWS Transform OpenSpec and Copilot/Cursor not as autocomplete but as a thinking partner to prototype faster scaffold services and harden artifacts to production Grounded in AI-first engineering and spec-driven development (SDD): you know how a specification becomes the source of truth for a service where autonomous and agentic workflows earn their keep and where they need guardrails instead of more freedom Able to assess a new framework on real criteria adoption effort IDE and coding-agent portability depth of AWS integration cost and how well it holds specs and code in sync then recommend a direction fast and defend the trade-offs to engineers and stakeholders alike

7 years in backend engineering with Java 2 years as a tech lead owning architecture code reviews and team mentoring Deep in modern Java (17) and the Spring ecosystem (Spring Boot) building microservices and contract-first REST APIs (OpenAPI) Experienced decomposing enterprise monoliths into microservices using the strangler-fig pattern keeping the legacy system running while carving out capabilities Solid on multi-tenancy application security and fine-grained authorization (JWT) and performance optimization (caching with Redis on hot paths) Cloud-native on AWS: containerized services on Kubernetes (EKS) with CI/CD pipelines as a daily practice A clean-code advocate: unit and integration testing code review and engineering best-practices across greenfield and modernization delivery A leader in the room: you make decisions with incomplete information invite the challenge and hold the line on quality when speed argues otherwise Quick to learn a new AI framework and quicker to pass it on you document it demo it and lift the whole teams baseline rather than keeping the edge to yourself

Selling Points

YOU WANT TO WORK WITH Java microservices carved out of an enterprise real-estate (lease management) platform integrated with shared data services PostgreSQL (Amazon Aurora) as the target data platform replacing legacy SQL Server as part of an enterprise D&T modernization programme An AWS cloud footprint EKS/Kubernetes and managed services with CI/CD for build and release Agentic AI tooling across the SDLC (Kiro spec-driven development AWS Transform) to prototype scaffold test and refactor and to measure automated vs. hand-crafted migration at scale An SDD toolchain you help choose rather than inherit: Kiro SpecKit and OpenSpec are on the table weighed on AWS integration against agent portability cost and drift control and no candidate has solved spec-to-code drift yet so closing that gap is part of the work Strangler-fig modernization with the hard problems front and centre: single data source per tenant data-per-microservice data integrity and module performance A cross-functional pod (PM UX/UI QA architecture) delivering AI-shaped features for a global enterprise client

Required Experience:

Senior IC