Senior AI Engineer

Design, build and operate production-grade agentic AI solutions using large language models, retrieval-augmented generation, multi-agent orchestration, tool use and prompt engineering.

Create reusable AI services, reference patterns and technical guardrails that allow squads across Zurich to deliver AI solutions more quickly, consistently and safely.

Establish evaluation pipelines, observability and cost controls so agent quality, reliability, performance and production run costs can be measured and actively managed.

Develop secure APIs and integration services that connect large language models with enterprise platforms, applying clear contracts, authentication, authorisation and data protection controls.

Assess architecture and system design options, define service boundaries and integration approaches, and present evidence-based recommendations covering security, reliability, scalability and cost.

Embed DevSecOps and secure-by-design practices through infrastructure as code, CI/CD automation, testing, least-privilege access, input validation and secrets management.

Important to your success – let’s grow together You are a curious and pragmatic engineer who enjoys turning ambiguity into working software. You bring a clear point of view, test ideas with evidence and collaborate well with product, design, subject matter experts and engineering teams. You are comfortable influencing technical outcomes without formal authority and enjoy lifting capability through code review, pairing and mentoring.

In order to be successful, you will have the following:

Significant software engineering experience, including hands-on experience designing, building and operating AI or large language model-based systems in production.

Production experience building AI agents with modern frameworks such as LangGraph, AWS Strands or AgentCore, together with Model Context Protocol and applied agentic AI patterns.

Deep AWS engineering capability across services such as Bedrock, AgentCore, Lambda, API Gateway, DynamoDB or RDS, SageMaker, ECS, S3 and IAM, supported by infrastructure as code using AWS CDK or Terraform.

Strong full-stack engineering capability using TypeScript, Node.js and Python for backend services, plus React or Next.js for frontend development, component design and state management.

Proven experience designing REST and GraphQL APIs, including API contracts, documentation and authentication patterns such as OAuth, OIDC, JWT and IAM.

Applied capability across AI evaluation, guardrails, observability, cost management, MLOps, architecture documentation, CI/CD automation, automated testing and security-first engineering.