16 days ago
London, United KingdomStaff+
Responsibilities
- Design and build scalable backend and cloud-native enterprise applications using Go and related technologies.
- Apply Domain-Driven Design, bounded contexts, event-driven architecture, service decomposition, and specification-driven development.
- Integrate production AI capabilities such as LLMs, retrieval-augmented generation, tool calling, prompt engineering, and agentic workflows into enterprise products.
- Design distributed systems, microservices, and APIs while maintaining reliability, security, maintainability, and operational excellence.
- Evaluate AI-enabled features for quality, reliability, performance, security, and operational readiness.
- Work with Product, Design, Engineering, and business stakeholders to solve customer problems and deliver measurable value.
- Mentor engineers, remove blockers, lead technical initiatives, and drive engineering quality and continuous improvement.
Requirements
- A degree in Computer Science, Software Engineering, or Information Technology.
- At least 6 years of experience in a similar role.
- Strong hands-on experience with Go and modern backend development; TypeScript and Node.js experience is preferred.
- Experience designing distributed systems, microservices, and RESTful APIs.
- Strong experience with Domain-Driven Design, bounded contexts, event-driven architecture, and service decomposition.
- Experience with Kubernetes, Kafka, Redpanda, PostgreSQL, MongoDB, AWS, and/or Azure.
- Experience integrating AI capabilities and Large Language Models into production enterprise software.
- Experience with RAG, tool calling, prompt engineering, agentic workflows, and AI feature evaluation.
- Experience with AI-assisted engineering tools such as GitHub Copilot, Cursor, or Claude Code.
- Understanding of authentication, authorization, secure software design, DevSecOps, automated testing, observability, and production operations.
- Strong analytical, problem-solving, communication, mentoring, and technical leadership skills.
- Demonstrable experience defining domain models and bounded contexts and using specifications to drive software design and implementation.
- React and modern frontend development, Enterprise SaaS or ERP products, Model Context Protocol, vector databases, AI observability, AI evaluation frameworks, or enterprise-scale AI platforms are beneficial.
Benefits
- Flexible and hybrid work opportunities.
- Inclusive global workplace with opportunities to collaborate across diverse teams and locations.
- Opportunity to build production AI-native enterprise software at scale and shape intelligent products for real-world customer challenges.
Tech Stack
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