Cloud Engineer with focus on AI/ML Optimizations

Our Company

Changing the world through digital experiences is what Adobe's all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours

The Opportunity

Are you ready to rethink Experience Management and transform your LLM and Generative Engine Optimization knowledge and takeaways into groundbreaking software? How hardworking are you about helping customers solving real-life problems unlocking the value that matters to them?

We're eager to welcome you to our Experience Success engineering team Together, we will craft the future of our Adobe LLM Optimizer customers

In collaboration with a larger distributed team of product and engineering experts, we build AI-first capabilities striving to deliver outstanding brand presence, agentic traffic acquisition, and high engagement for users referred by LLMs.

As a member of our team, you'll lead and develop customer-facing GEO-focused strategies that transform manual operations into efficient AI-first software.

What will you do

As a Software Engineer, you will directly contribute to core features of the product by building cloud services that integrate AI for solutions that drive high impact on our customers.

Discover success metrics for customers by analyzing meaningful data from various sources. Be in charge of comprehensive technical audits and improve strategies to optimize the experiences of our customers taking into consideration GEO, SEO, accessibility crawl-ability, index-ability and demonstrating insights for future automation.

Turn your findings into solid hypotheses that will be meaningful at wider customer scale. Automate your hypotheses into self-learning AI-first software with goal to improve conversion, website/off-site performance, GEO and user experience.

Manipulate and build services that integrate traditional ML and generative AI to extract insights from large data sets.

Design and implement prompt engineering strategies to optimize model performance.

Utilize Retrieval-Augmented Generation (RAG) and related techniques to enhance model output.

Collaborate with cross-functional teams to identify and address AI-related challenges.

Demonstrate the latest innovations in generative AI to stakeholders.

What you need to succeed

Excellent problem-solving skills, strong communication, and a proactive, collaborative approach, growing in fast-paced environments. Technical Skills:

Advanced degree in Computer Science, Data Science, Machine Learning, or a related field.

Experience with JavaScript or Python and proficiency with modern frameworks.

Proven expertise in crafting and developing scalable and resilient applications using concepts like CDNs, Cache, Server Side Rendering, Lambda functions, Containers, Queues, Workers, APIs, all in Cloud Platforms(Azure, AWS)

Experience in working with SQL & NoSQL Databases

Experience in integrating ML/Generative AI models.

Knowledge in both building but also operating a service: CI/CD deployments, monitoring and alerting, Kubernetes-based deployments

Pluses:

Experience in machine learning, data science or experience working with Generative AI models.

Proficiency in ML frameworks like PyTorch and TensorFlow.

Proven experience with Large Language Models (e.g. GPT, BERT) and prompt engineering.

Ability to quickly generate working code with a Generative AI coding copilot.

Expertise in fine-tuning and deploying AI models in production environments.

Strong knowledge of Retrieval-Augmented Generation (RAG) and related techniques.

Familiarity with marketing performance metrics and their application in AI models.

Ability to suggest new projects and make a case for their benefits to our business.

Experience & Education:

Bachelor's or equivalent experience in CS or related field

5+ years of proven experience working with the above mentioned tech stack

Portfolio of work (GitHub, live projects)

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