Senior AI Platform Engineer
Adobe
About the role
The Opportunity
Adobe empowers individuals and organizations to create exceptional content effortlessly. The AI for Engineering team builds a scalable, production‑grade AI platform that powers creativity across design, imaging, motion, and personalization.
We are seeking a Staff Engineer - AI for Engineering to design and build the next‑generation AI systems that bring intelligent, adaptive, and agentic experiences to Adobe Express.
This role is ideal for an engineer who deeply understands how modern LLMs and generative models behave in real‑world systems — including reasoning patterns, tool use, prompt dynamics, failure modes, and orchestration strategies — and can translate that understanding into scalable, production‑ready platforms.
You will define and build the end‑to‑end architecture that enables Agentic AI solutions solving real engineering problems—spanning model orchestration, tool integration, memory systems, inference services, data flows, evaluation loops, and real‑time decision systems.
This is a systems‑first AI role focused on building intelligent platforms.
What You’ll Do
- Build scalable Agentic AI platforms that empower developers, significantly boost engineering productivity, and accelerate AI adoption across the organization.
- Architect and evolve the AI platform powering Adobe Engineering — with a strong emphasis on Agentic AI systems and LLM‑native architectures.
- Design and implement scalable orchestration layers that coordinate LLMs, tools, APIs, memory stores, and multi‑step reasoning workflows.
- Build production‑grade agent frameworks that support planning, task decomposition, tool invocation, multi‑agent collaboration, and persistent memory.
- Develop high‑performance inference and runtime systems with strong guarantees around latency, reliability, observability, and cost efficiency.
- Design evaluation and feedback systems that measure reasoning quality, task success, hallucination rates, and agent behavior — enabling rapid iteration and continuous improvement.
- Integrate first‑party and third‑party foundation models into cohesive, adaptive systems using routing, model selection, guardrails, and fallback strategies.
- Design data flows, session‑level intelligence, and contextual memory systems that allow agents to operate coherently across interactions.
- Partner with applied research, product, and platform teams to bring intelligent agentic capabilities into real developer‑facing experiences.
- Drive architectural strategy for AI for Engineering — connecting models, reasoning engines, tools, and data streams into adaptive AI systems.
- Mentor senior engineers in modern AI system design, LLM orchestration patterns, and agent platform architecture.
What You’ll Bring
- 10+ years of experience building large‑scale distributed systems, AI platforms, or intelligent service architectures.
- Deep understanding of how LLMs behave in production environments — including prompting strategies, reasoning chains, tool usage, grounding techniques, hallucination mitigation, guardrails, and evaluation patterns.
- Strong experience building AI‑powered systems using LLM orchestration frameworks, model routing strategies, and multi‑model pipelines.
- Hands‑on experience designing agentic systems — including reasoning loops, memory persistence, tool integration, state management, and multi‑agent coordination.
- Proven expertise in building scalable, cloud‑native, microservices‑based architectures with strong observability and reliability.
- Experience designing evaluation systems for generative AI quality, task completion, and behavioral robustness.
- Proficiency in TypeScript, Python and at least one systems language (Java, Go, C++), with experience building production AI services.
- Strong systems thinking — ability to connect model capabilities, runtime constraints, and product requirements into coherent architectures.
- Excellent multi‑functional communication skills, with experience influencing architectural direction across research and engineering teams.
Preferred Qualifications
- Experience architecting AI assistants, copilots, or agent platforms in production environments.
- Experience working with multimodal generative systems (text, image, video, motion).
- Familiarity with tool‑augmented LLM systems, RAG architectures, vector databases, and contextual memory systems.
- Exposure to evaluation frameworks for generative AI quality and safety.
- Experience contributing to open‑source AI frameworks or publishing technical thought leadership.
About Adobe
Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry‑leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.
Additional Information
Let’s Adobe together
At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.
Equal Employment Opportunity
Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.
Accessibility
Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call +1 408‑536‑3015.
AI Use Guidelines for Interviews
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
Expected Pay Range
- U.S. pay range: $172,500 – $306,625 annually (varies by location, knowledge, skills, experience).
- California: $211,800 – $306,625.
Non‑sales roles are expressed as base salary plus short‑term incentives (Annual Incentive Plan). Certain roles may be eligible for long‑term incentives in the form of a new‑hire equity award.
State‑Specific Notices
- California – Fair Chance Ordinances: Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
- Colorado – Application Window Notice: If this role is open to hiring in Colorado, the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations.
- Massachusetts – Legal Notice: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.
Requirements
- 10+ years of experience building large-scale distributed systems, AI platforms, or intelligent service architectures.
- Deep understanding of how LLMs behave in production environments — including prompting strategies, reasoning chains, tool usage, grounding techniques, hallucination mitigation, guardrails, and evaluation patterns.
- Strong experience building AI-powered systems using LLM orchestration frameworks, model routing strategies, and multi-model pipelines.
- Hands-on experience designing agentic systems — including reasoning loops, memory persistence, tool integration, state management, and multi-agent coordination.
- Proven expertise in building scalable, cloud-native, microservices-based architectures with strong observability and reliability.
- Experience designing evaluation systems for generative AI quality, task completion, and behavioral robustness.
- Proficiency in TypeScript, Python and at least one systems language (Java, Go, C++), with experience building production AI services.
- Strong systems thinking — ability to connect model capabilities, runtime constraints, and product requirements into coherent architectures.
- Excellent multi-functional communication skills, with experience influencing architectural direction across research and engineering teams.
Responsibilities
- Build scalable Agentic AI platforms that empower developers, significantly boost engineering productivity, and accelerate AI adoption across the organization.
- Architect and evolve the AI platform powering Adobe Engineering — with a strong emphasis on Agentic AI systems and LLM-native architectures.
- Design and implement scalable orchestration layers that coordinate LLMs, tools, APIs, memory stores, and multi-step reasoning workflows.
- Build production-grade agent frameworks that support planning, task decomposition, tool invocation, multi-agent collaboration, and persistent memory.
- Develop high-performance inference and runtime systems with strong guarantees around latency, reliability, observability, and cost efficiency.
- Design evaluation and feedback systems that measure reasoning quality, task success, hallucination rates, and agent behavior — enabling rapid iteration and continuous improvement.
- Integrate first-party and third-party foundation models into cohesive, adaptive systems using routing, model selection, guardrails, and fallback strategies.
- Design data flows, session-level intelligence, and contextual memory systems that allow agents to operate coherently across interactions.
- Partner with applied research, product, and platform teams to bring intelligent agentic capabilities into real developer-facing experiences.
- Drive architectural strategy for AI for Engineering — connecting models, reasoning engines, tools, and data streams into adaptive AI systems.
- Mentor senior engineers in modern AI system design, LLM orchestration patterns, and agent platform architecture.
Benefits
Skills
Don't send a generic resume
Paste this job description into Mimi and get a resume tailored to exactly what the hiring team is looking for.
Get started free