Senior Software Engineer - Automation & Tooling
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What you'll do
- Design, develop, and maintain robust automation frameworks, tools, and scripts to enhance engineering efficiency and product quality. Write production-grade code and actively contribute to the test automation ecosystem.
- Provide architectural input for automation solutions, ensure scalability and maintainability, and set coding standards for QA automation. Act as a go-to technical leader while remaining actively involved in code contributions.
- Partner with Product Managers, Engineering Managers, Engineers, QA Managers, and QA peers across multiple pods to identify quality challenges, share solutions, and drive org-wide improvements.
- Identify gaps in QA processes and tooling; design and implement innovative solutions to improve testing practices. Drive the evaluation, adoption and integration of new technologies, frameworks, and methodologies within the Automation & Tooling team.
- Own complex quality issues across pods; facilitate discussions and workshops to drive resolution and implement long-term solutions.
- Mentor junior engineers and QA peers in automation best practices. Run knowledge-sharing sessions to spread technical expertise across the organization.
- Track and analyze QA-related KPIs; leverage data to identify improvements and report progress on automation and quality initiatives.
- Align QA automation strategies with end-user needs, ensuring test coverage and quality improvements directly support the customer experience.
What they're looking for
- Bachelor’s degree in computer science, Engineering, or equivalent experience.
- 8+ years in Quality Engineering or Software Development, with strong emphasis on test automation and tooling.
- Strong software engineering background with proven coding expertise (Python required; Java, JavaScript, or similar languages a plus).
- Demonstrated ability to architect and maintain automation frameworks at scale.
- Experience integrating automation into CI/CD pipelines and modern DevOps environments.
- Track record of contributing both strategically (process/tooling improvements) and technically (hands-on coding).
- Experience mentoring engineers and influencing QA practices across teams or pods.
Nice to have
- Hands-on experience developing AI -powered applications, especially using RAG architectures for knowledge retrieval and augmentation.
- Familiarity with LangChain or similar frameworks for building LLM-powered workflows.
- Experience with Model Context Protocols (MCPs) or related agent orchestration approaches.
- Strong Python skills with modern ML/AI libraries (e.g. Hugging Face, OpenAI API, Llama Index).
- Experience applying AI in QA/automation contexts (e.g., intelligent test generation, anomaly detection, defect classification).
- Understanding of MLOps practices (model deployment, monitoring, versioning, integration with CI/CD).
- Awareness of ethical AI practices (bias, explainability, model governance).
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Senior Software Engineer - Automation & Tooling
Key Responsibilities
- Design, develop, and maintain robust automation frameworks, tools, and scripts to enhance engineering efficiency and product quality. Write production-grade code and actively contribute to the test automation ecosystem.
- Provide architectural input for automation solutions, ensure scalability and maintainability, and set coding standards for QA automation. Act as a go-to technical leader while remaining actively involved in code contributions.
- Partner with Product Managers, Engineering Managers, Engineers, QA Managers, and QA peers across multiple pods to identify quality challenges, share solutions, and drive org-wide improvements.
- Identify gaps in QA processes and tooling; design and implement innovative solutions to improve testing practices. Drive the evaluation, adoption and integration of new technologies, frameworks, and methodologies within the Automation & Tooling team.
- Own complex quality issues across pods; facilitate discussions and workshops to drive resolution and implement long-term solutions.
- Mentor junior engineers and QA peers in automation best practices. Run knowledge-sharing sessions to spread technical expertise across the organization.
- Track and analyze QA-related KPIs; leverage data to identify improvements and report progress on automation and quality initiatives.
- Align QA automation strategies with end-user needs, ensuring test coverage and quality improvements directly support the customer experience.
Qualifications
- Bachelor’s degree in computer science, Engineering, or equivalent experience.
- 8+ years in Quality Engineering or Software Development, with strong emphasis on test automation and tooling.
- Strong software engineering background with proven coding expertise (Python required; Java, JavaScript, or similar languages a plus).
- Demonstrated ability to architect and maintain automation frameworks at scale.
- Experience integrating automation into CI/CD pipelines and modern DevOps environments.
- Track record of contributing both strategically (process/tooling improvements) and technically (hands-on coding).
- Experience mentoring engineers and influencing QA practices across teams or pods.
Skills and Competencies
- Excellent coding and debugging skills; strong grasp of software engineering principles.
- Ability to design and document complex automation frameworks and tools.
- Strong problem-solving, analytical, and architectural skills.
- Excellent communication and interpersonal abilities; able to influence without direct authority.
- Knowledge of Agile and DevOps methodologies.
Bonus / Preferred Skills in AI/ML
- Hands-on experience developing AI -powered applications, especially using RAG architectures for knowledge retrieval and augmentation.
- Familiarity with LangChain or similar frameworks for building LLM-powered workflows.
- Experience with Model Context Protocols (MCPs) or related agent orchestration approaches.
- Strong Python skills with modern ML/AI libraries (e.g. Hugging Face, OpenAI API, Llama Index).
- Experience applying AI in QA/automation contexts (e.g., intelligent test generation, anomaly detection, defect classification).
- Understanding of MLOps practices (model deployment, monitoring, versioning, integration with CI/CD).
- Awareness of ethical AI practices (bias, explainability, model governance).
Company Summary
Zeta Global is a data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.
Zeta Global is a leading AI-powered marketing technology company that enables enterprise brands to acquire, grow, and retain customers through intelligent, data-driven engagement. At the center of its innovation is the Zeta Marketing Platform (ZMP), which unifies customer data, identity, and advanced analytics to transform billions of data signals into actionable marketing intelligence and measurable business outcomes.
Publicly traded on the New York Stock Exchange (NYSE: ZETA), Zeta is redefining modern marketing with Athena by Zeta™, a superintelligent, conversational agent embedded in ZMP that personalizes the marketer’s workspace, surfaces platform generated insights through natural dialogue and recommends next-best actions to help brands accelerate and optimize their marketing outcomes.
Company
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