AIML Engineer – GenAI Assistant & Experience Engineering

The Opportunity

Werelooking for anAI/ML Engineerwho is excited to build intelligent features using whatever approach solves the problem best.

Some solutions will useLLMs and generative AI some will rely ontraditional ML some will beheuristic or rules-based and many will behybrid systemsthat combine them.

Your job is to evaluate the problem choose the right approach and deliver high-quality scalable solutions that improve user experiences.

In this roleyoullbuild models design prompts develop services run evaluations and ship features end-to-end. This is a hands-on applied engineering role with broad ownership whereyoullwork across modeling service development and lightweight ops.

WhatYoullDo

AI ML & Hybrid Solution Development

• Build anditerate onsolutions using thefull spectrumof approaches: LLMs classical ML heuristics rules engines retrieval systems or combinations thereof.

• Design train and evaluate classical ML models whereappropriate and integrate fine-tune (via prompting or adapters) and evaluate partner-provided LLMs for generative AI classification search and content understanding use cases

• Develop prompting strategies multi-step prompt workflows and agents that power interactive AI experiences.

• Build hybrid pipelines that combine deterministic logic with AI/ML components for predictable reliable outcomes.

Service & Feature Engineering

• Implement backend services and inference pipelines for the AI Assistant across Experience Cloud.

• Build RAG systems model-serving layers experimentation hooks and scalable APIs.

• Partner withfrontendengineers and product teams to turn concepts into shipped features.

Evaluation Data and Light Ops

• Build automated evaluation pipelines to measure quality safety latency and reliability.

• Prepare datasets for evaluation fine-tuning and experimentation.

• Deploy models and services using CI/CD containers and cloud workflows.

• Monitor performance and iterate quickly based on data and user signals.

While this is not a dedicated opsroleyou should be able to own andoperateyour work end-to-end as projects require.

Cross-Functional Collaboration

• Work closely with Product EngineeringDesignand ML teams to explorenew ideasand deliver customer-facing features.

• Help define guidelines for AI/ML development evaluation and hybrid system building.

• Contribute to shared tools that accelerate experimentation and improve developer productivity.

What You Bring

• 5years experienceinmachine learning applied AI engineeringIRor full-stack intelligent feature development prioritizingexperience with core ML problem-solving such as building/designing or debugging predictive models (over operational pipelines and monitoring)

• Hands-on experience with both LLM-based and traditional ML techniques and the judgment to select the appropriate tool for the job.

• Strong software engineering fundamentals and experience building production services (Node Python TypeScript Go or similar).

• Ability to design evaluation frameworks run experiments and iterate rapidly.

• Comfortable owning features from prototype production including monitoring and optimization.

• Excellent communication and collaboration skills;thrivesinenvironments with ambiguity and autonomy.

Nice to Have

• Experience with hybrid LLM deterministic systems vector search or orchestration tools.

• Knowledge of Adobe Experience Cloud or other enterprise SaaS ecosystems.

• Contributions to open-source AI/ML tools model-serving frameworks or evaluation libraries.

• Prior startup or high-velocity product development experience.