
Lead AI Automation Engineer
SEPHORA • San Francisco, California, United States
Role & seniority: Lead AI Automation Engineer (senior/lead level)
Stack/tools: Agentic AI, Generative AI, end-to-end SDLC automation; AI agents for code generation, automated testing, CI/CD integration; MLOps; LLM orchestration; RAG; prompt engineering; vector DBs; relational SQL and NoSQL; Hadoop, Spark, Kafka; Scala, Python; PyTorch, TensorFlow, Keras; Databricks; cloud platforms (Azure, AWS); APIs; distributed systems
Top 3 responsibilities
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Architect, build, and improve end-to-end SDLC with AI Agents for automated requirements analysis, code generation, test script creation, and defect risk identification
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Integrate AI-driven quality checks (code reviews, security scans, performance) into CI/CD; monitor production for anomalies and self-healing
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Lead innovation pilots/POCs; establish scalable MLOps practices; mentor teams on GenAI and Agentic AI adoption
Must-have skills
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10+ years software engineering experience; 3+ years applying AI/ML/GenAI to workflows
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Deep knowledge of LLMs, Agentic AI concepts (orchestrated agents, RAG, prompt engineering, vector DBs)
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Experience with SQL/NoSQL; Hadoop, Spark, Kafka; Scala, Python; cloud platforms (Azure/AWS); Databricks
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Deep learning frameworks (PyTorch, TensorFlow, Keras); OO/functional languages (Python, Java, C++, Scala)
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Experience productizing end-to-end ML systems; familiarity with distributed service architectures and API design
Nice-to-haves
- Track record leading pilots/POCs; strong
Full Description
Technology Our technology team works fast and smart. With San Francisco as our home, we take bringing new tech to market seriously. We love what we do, and we have fun doing it. The Technology group is comprised of motivated self-starters and true team players who are integral to the growth of Sephora and our future success.
Your role at Sephora We are seeking an experienced Lead AI Automation Engineer with deep interest and expertise in Agentic AI, Generative AI, and automation frameworks to drive innovation in our software development lifecycle (SDLC). This role will focus on designing, developing, and implementing AI-powered solutions that enhance quality, accelerate delivery, and transform how engineering teams build, test, and release products. As a Lead AI Automation Engineer... Architect, build, maintain, and improve end-to-end SDLC – AI Agents Implement end-to-end solutions for automated testing, performance testing and A/B testing Collaborate with Product, PMO, Engineering, and DevOps on planning new capabilities Establish scalable, efficient, automated processes for data analysis, model development, validation, and implementation Write efficient and well-organized software to ship products in an iterative, continual-release environment Actively participate in code review and test solutions to ensure it meet best practice specifications Write efficient and well-organized software in an iterative, continual-release environment Actively participate in code review and test solutions to ensure it meets best practice specifications. Contribute to and promote good software engineering practices across the team Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences
Responsibilies
- Provide hands-on technical expertise, guidance, and mentorship to develop Agentic AI driven quality solutions, across multiple SDLC phases. Design and implement AI agents to autonomously analyze requirements, generate code, generate test scenarios, create/maintain automated test scripts, and identify gaps, risks and potential defects early in the cycle
- Partner with DevOps and SRE teams to integrate AI-driven quality checks into CI/CD pipelines. Develop AI agents for code reviews, security scans, performance optimization and monitor production environments for anomaly detection and self-healing recommendations
- Lead innovation pilots and POCs, evaluating emerging AI/ML tools, and recommend scalable adoption strategies. Establish and maintain MLOps practices for the AI lifecycle (model training, deployment, monitoring, and governance) and automate processes across the engineering pipeline. Coach and mentor technical teams on leveraging Gen AI and Agentic AI for productivity and quality improvements
We're excited about you if you if you have
- 10 years of experience in the Software engineering space
- 3+ years of proven experience applying AI/ML or GenAI solutions to Develop workflows
- Deep understanding of LLM models, Agentic AI concepts (LLM orchestration, autonomous agents, RAG, prompt engineering, vector DBs), and AI/ML toolkits to solve quality engineering challenges
- Experience working with a variety of relational SQL and NoSQL databases
Experience working with: Hadoop, Spark, Kafka, Scala, Python Knowledge of cloud platforms, Experience with Azure, AWS or equivalent cloud platforms Hands-on Experience working with Databricks Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras or similar
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala Industry experiences building and productionizing creative end-to-end Machine Learning systemsExperience with building and operationalizing a featureExperience working with distributed systems, service-oriented architectures, and designing APIs/ API