The Opportunity
Adobe Express helps people and teams create standout content with ease. The AI Foundations team builds the core AI platform that powers creativity across design, imaging, motion, and personalization. We’re looking for an engineer to help develop and scale the AI infrastructure behind these experiences. This role is a strong fit for someone with solid software engineering fundamentals, exposure to ML systems, and interest in building reliable large-scale platforms that support modern AI products.
You’ll work with experienced engineers to build production systems that power Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI. Your work will contribute to important layers of the platform, including model integration, inference services, data pipelines, storage and caching systems, analytics, and evaluation tooling.
What You’ll Do
- Contribute to the development of core platform components that support AI experiences in Adobe Express.
- Build and improve backend services, microservices, and workflows that connect models, APIs, data systems, and product features.
- Help develop data and inference pipelines for training, evaluation, fine-tuning, and deployment of ML models.
- Support runtime systems for inference and orchestration with attention to reliability, observability, and performance.
- Work on storage, caching, and data-access patterns to improve efficiency, scalability, and cost.
- Collaborate with engineers, researchers, and product teams to deliver production-ready AI capabilities.
- Participate in debugging, testing, monitoring, and operational improvements for AI platform services
What You'll Bring
- 3+ years of experience in software engineering, backend infrastructure, data systems, ML infrastructure, or related areas.
- Good understanding of distributed systems fundamentals, backend services, and scalable system design.
- Experience building or supporting APIs, data pipelines, or event-driven systems.
- Proficiency in Python, Java, C++, or Go.
- Familiarity with cloud environments, service deployment, and production engineering practices.
- Exposure to ML systems or LLM-based applications, including model inference, orchestration, or evaluation, is a plus.
- Strong problem-solving skills and the ability to work well in a collaborative team environment.
- Clear communication skills and willingness to learn from cross-functional partners.
Preferred Qualifications
- Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or a related technical field.
- Experience with technologies such as Kafka, Spark, Flink, or similar distributed data frameworks.
- Exposure to generative AI systems such as LLMs, multimodal models, or diffusion models.
- Familiarity with MLOps concepts such as experiment tracking, model deployment, or evaluation workflows.
- Interest in agentic AI concepts such as tool use, task planning, or memory systems.
Expected Pay Range:
Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this positionis $125,600 -- $234,150 annually. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
In California, the pay range for this position is $161,700 - $234,150
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
