At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together.
You will join our ML & AI ART as a Senior AI Test Automation Engineer, responsible for the technical test automation solution supporting our AI and MLOps platform. The platform powers AI-driven capabilities across the Bank including RAG systems, LLM-based assistants, agentic workflows, and ML pipelines serving business-critical use cases. You will own the architecture, implementation, and execution of our test automation frameworks, covering both traditional software components (APIs, UIs, data pipelines) and emerging AI/ML-specific behaviour , and act as the Test Automation Ambassador within the ART. You will work within the Bank's Test Strategy, while owning the technical depth and hands-on delivery of automation for your platform.
Define and evolve the technical test automation approach and framework architecture for the ML & AI ART, aligned with the Bank's Test Strategy and Test Policy
Design reusable, scalable test automation patterns (page objects, API clients, test data builders) that other engineers across squads can adopt, ensuring technical consistency of test automation across the ART
Analyse and evaluate requirements, Features, and Stories for testability during PI Planning, Backlog Refinement, and Iteration Planning
Derive test cases from technical and risk analysis of both functional and non-functional requirements (reliability, performance, security, usability, robustness), selecting appropriate test techniques and automation scope based on risk, coverage goals, and ROI
Automate identified test cases using Python-based frameworks — Playwright-Python for UI, requests + pytest for APIs, Behave or pytest-bdd for BDD/Gherkin — applying clean code principles, reusability, readability, and stability
Design and implement AI/ML-specific test cases: evaluation pipelines for LLM outputs
Build and maintain contract tests (e.g. Pact) for platform APIs and microservice boundaries
Integrate and orchestrate automated tests in GitLab CI/CD pipelines, including merge request pipelines, GitLab runners
Leverage Docker and Kubernetes to provision isolated, reproducible test environments
Plan, schedule, and trigger automated test executions across environments (DEV, INT, UAT, pre-PROD) — including regression suites, smoke tests, release executions, and on-demand runs tied to merge requests and PI milestones
Monitor execution health, investigate and quarantine flaky tests, and maintain a low false-positive rate to keep quality signals trustworthy
Triage execution results, raise defects in Jira with evidence (logs, traces, screenshots, videos), and communicate quality signals to the squad, Product Owner, and Test Manager
Produce execution evidence (run metadata, artefacts, reports) suitable for audit and release governance, in line with the Bank's Test Policy and retention requirements
Contribute actively to PI Planning, System Demos, Inspect & Adapt, and other SAFe ceremonies as part of the ML & AI ART
Ensure end-to-end traceability from Jira Features and Stories automated tests defects test results, leveraging the Bank's test management integration
Author and maintain BDD scenarios in Gherkin, linked to acceptance criteria on Stories
Collaborate closely with Product Owners, Scrum Masters, ML Engineers, MLOps Engineers, and Data Engineers across squads
Align work with the Bank's Test Strategy, and reporting requirements, supporting audit-ready artefacts, traceability matrices, and test progress reporting
S upport root cause analysis of defects using logs and traces
Act as Test Automation Ambassador within the ML & AI ART consulting squads on automation design, framework usage, tooling choices, and test data strategy
Prepare test data, ensuring synthetic or anonymised data is used wherever possible to meet confidentiality expectations
Design AI/ML-specific test datasets where needed
Own test maintenance and refactoring in response to UI, API, model, or prompt changes, ensuring continued compliance with access controls and test environment policies
Proven expertise in Python-based test automation: Playwright-Python (UI), Behave or pytest-bdd (Gherkin/BDD), requests + pytest (API/service validation practical equivalence to REST-Assured)
Demonstrated ability to design and own test automation frameworks, not just write test scripts including reusable utilities and maintainability patterns
Hands-on experience integrating and executing automated tests within CI/CD pipelines, ideally GitLab or equivalent enterprise platforms
Experience with distributed test execution, parallelisation, flaky-test management, and modern reporting tools (Allure, pytest-html, or equivalent)
Solid grasp of Git and version control workflows, clean code principles, and code review culture
Working knowledge of Docker; familiarity with Kubernetes basics (jobs, namespaces)
Exposure to testing AI/ML systems, or strong motivation to develop this expertise: evaluation of LLM outputs, handling non-deterministic responses, evals for RAG and agentic workflows
Understanding of API design, microservices, event-driven architectures, and authentication layers
Sound understanding of SAFe and DevOps principles; experience operating in an Agile Release Train is a plus
Experience with Jira for Story/Feature tracking and test management integration (Xray, Agile Hive)
Demonstrated end-to-end thinking — connecting user journeys, data flows, authentication layers, and system boundaries
Comfortable working within an established Test Strategy, collaborating with Test Managers on execution planning, reporting, and compliance
Demonstrated awareness of information security, data privacy, and compliant test data handling in regulated environments
Collaborative team player with strong ownership takes automation problems from analysis to execution to resolution with minimal supervision
Strong communicator able to work effectively with engineers, Product Owners, Scrum Masters, Architects, and Test Managers
Strong organisational skills, structured, reliable
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Minimum 5–7 years in Test Automation with substantial hands-on Python experience, including demonstrated framework design, ownership, and test execution at scale (not only script-level contributions)
Experience in a regulated environment (financial services, healthcare, pharma) strongly preferred
Certifications in ISTQB (Foundation as baseline)
SAFe (SP, SSM, or equivalent), or DevOps disciplines are a plus
Exposure to AI/ML systems through testing, development, or applied projects is a strong plus; appetite to develop deep AI/ML testing expertise is essential
Fluency in English; Spanish is a plus
We are looking forward to receiving your full job application through our online application tool.
