Studio Dev Ai

**ABOUT THE OPPORTUNITY**

**Who you will work with**:
This is a new senior-level role that will interact closely with globally-distributed UI developers, back-end cloud developers, edge developers, data engineers, data scientists, architects, and stakeholders across the various Studio groups in Engineering. We commonly use swarming to help the team learn more quickly and get things done while enjoying it. You will also collaborate cross-functionally as needed with product line managers, professional services, technologists, and customer-facing teams. You will report to a regional manager within the Studio AI directorate in Engineering.

**What you’ll do / your responsibilities**:

- Design a comprehensive V&V strategy spanning all aspects of building quality into the platform, including use of reviews and static & dynamic analysis tools
- Support your team in defining acceptance criteria so the epics and stories are unambiguous, testable, & verifiable
- Lead your team on scoping & autonomously managing V&V-related project priorities, deadlines, and deliverables
- Define and implement test cases spanning all development responsibilities for V&V (unit tests, feature tests, integration tests, and regression tests)
- Compose and automate tests using common, relevant test frameworks, wherever it makes sense to do so
- Ensure that automated test code clearly identifies failure and points less-technical users towards root cause
- Integrate test validation scripts into the CI/CD/CT pipeline and test automation framework
- Measure, report, and continually improve test coverage and effectiveness.

The tests you will plan, define, execute, and automate will span V&V for:
This is not a siloed team situation where developers will throw (possibly untested) code over the wall to you; you will be a full member of the cross-functional team. You will also have opportunities to:

- Pair up with developers on your AI team to mentor and up-level them in knowledge and skills for ways (not limited to testing) to effectively build quality into their code, to prevent defects and/or detect defects as early as possible
- Collaborate and advise AI developers on how to build testability into the software the teams deliver
- Participate in hiring, then mentoring, less-experienced SDETs as the AI team grows
- Evaluate and justify make/buy/reuse technology selection decisions for test automation capabilities
- Contribute to overall AI strategy for improving V&V effectiveness and product quality

**Qualifications - MUST HAVE**:

- BE/BTech in Computer Science, Computer / Electrical / Software / Systems / Mechanical Engineering, Operations Research, Data Science, Applied Math / Physics, or another STEM field
- Advanced degrees (e.g. ME/MTech/MS, MBA, or Ph.D.) are appreciated, but not required
- 10 years working in software development, 4+ in a V&V-focused role _(career gaps are ok; life happens)_
- Programming skills in at least one higher-level language _(e.g., Python, C/C++) _and SQL
- Ability and experience to analyze business use cases to produce effective test case coverage:

- understanding the key personas and user journeys for the software, and how to evaluate both functionality and architectural qualities from the user’s perspective
- ‘think like a tester and put yourself into your users’ shoes
- knowing how to test to find all the ways it doesn’t work [well], vs. testing to show that the happy path works
- Exceptional, inclusive, collaborative team player comfortable with working in diverse, distributed agile environments, pairing with developers, and taking the initiative to collaborate with the cross-functional team
- Self-managed, fast learner with the desire and ability to master new technologies
- Blend of technical expertise and soft skills, including effective & flexible communication skills in English

**Core Competencies and Demonstrated Success - **You should have **most or all** of these:

- A basic or better understanding of cybersecurity principles and practices, CVEs, and vulnerability scanning tools
- Demonstrated history of defining a comprehensive test strategy for cloud-based products
- Strong understanding of secure software product development lifecycle (including requirements and verification)
- Experience using common test automation frameworks, static analysis tools, and dynamic analysis tools
- Experience working with RESTful APIs, OpenAPI, and Swagger; familiarity with API gateways such as Kong is a plus
- Experience handling data with a cloud-based or on-premises big data platform _(e.g. AWS, Azure, GCP, or equivalent open-source technologies)_
- Comfortable using CM/CI/CD/CT tools (Git, GitHub, GitLab, Jenkins, Tekton) and IaC (Terraform, Helm charts)
- Proficiency with Kubernetes, Docker, and cloud deployment technologies
- Good understanding of the concept of Cost of Quality and driving a positive influence on product delivery

**_ Note_**_: Although this is primarily a development testin