Senior Golang Engineer - Generative AI Platform
We are seeking a Senior Golang Engineer to join a growing team focused on building enterprise-scale Generative AI platforms and developer tooling. This is an opportunity to work at the intersection of cloud-native engineering, distributed systems, and AI, helping deliver the next generation of AI-enabled capabilities within a global financial services environment. We're looking for strong T-shaped engineers with deep expertise in Golang and broad engineering capability across Kubernetes, platform engineering, DevOps, scalability, and distributed systems. Commercial AI experience is not required, but a genuine interest in Generative AI and emerging technologies is essential.
Responsibilities
- Design, develop and operate scalable backend services using Golang.
- Build cloud-native platforms supporting Generative AI and LLM-powered applications.
- Develop reusable libraries, frameworks and internal developer tooling.
- Design and implement distributed systems with a focus on reliability, performance and scalability.
- Collaborate with platform, infrastructure and AI engineering teams.
- Drive engineering best practices, observability, automation and operational excellence.
- Mentor engineers and contribute to technical leadership across the team.
Qualifications
- Strong commercial experience developing software in Golang.
- Deep understanding of distributed systems and backend architecture.
- Strong Kubernetes knowledge and experience running applications in production.
- Experience with microservices, APIs, event-driven architectures and cloud-native technologies.
- Strong understanding of CI/CD, DevOps and platform engineering principles.
- Experience building highly scalable, resilient systems.
- Excellent communication and stakeholder management skills.
Candidates should possess a strong understanding of Kubernetes concepts equivalent to the core topics covered in Chapters 1 6 of: Kubernetes in Action Including:
- Pods, Deployments and ReplicaSets
- Services and Networking
- ConfigMaps and Secrets
- Resource Management
- Health Checks and Application Lifecycle
- Namespaces and Workload Management
- Kubernetes Architecture and Operational Concepts
Commercial AI experience is not required. However, candidates should demonstrate:
- Strong interest in Generative AI and LLM technologies.
- Understanding of modern AI tooling and frameworks.
- Experience experimenting with AI-assisted development tools.
- Curiosity around agentic systems, RAG architectures, and enterprise AI adoption.
Desirable Skills
- Experience with AI/ML platforms or developer productivity tooling.
- AWS, Azure or GCP experience.
- Experience with Kafka, messaging systems or event-driven architectures.
- Financial services or regulated industry experience.
- Platform Engineering or Internal Developer Platform experience.