Core Agent Engineer

About the Role

Adobe is reimagining the future of creativity, where generative AI, intelligent agents, and human imagination work hand in hand. As a Senior Full Stack Engineer, Agentic Product, you will be a key technical contributor for Adobe's up-and-coming AI-native experience. You will own hands-on buildout of the agent across the full stack and across Adobe's target platforms, from desktop and mobile to web and embedded surfaces. This is a rare opportunity to build the engineering foundations of Adobe's soon-to-be most visible AI product.

Key Responsibilities

• Own full-stack implementation across Adobe's Agentic Product — from LLM integration and agentic reasoning layers, to API surfaces, client runtimes, and platform-specific delivery on desktop, mobile, and web.
• Contribute to the production buildout of the agent: translating prototype-quality capabilities into robust, scalable, maintainable systems.
• Drive hands-on implementation of high-leverage components — including model orchestration, tool use, multi-step task execution, context and memory management, and agent evaluation infrastructure.
• Champion the adoption of AI-assisted engineering practices — using tools like Claude Code, Codex, and emerging agentic development platforms to accelerate implementation and raise code quality. Model new workflows where AI is a first-class collaborator.
• Contribute to developer experience: tooling, local development loops, CI/CD ergonomics, and scaffolding.
• Stay current with the model capabilities ecosystem, evaluating new LLM approaches and frameworks.
• Help build and maintain the evaluation and quality framework for agent behavior — the evals, benchmarks, and feedback loops.
• Partner with Engineering and Product leadership to translate product ambitions into technically grounded delivery.
• Collaborate across Adobe's platform, infrastructure, data, and security teams to ensure the Agentic Product is built on a foundation that supports guardrails, data protection, observability, and operational requirements.
• Raise the bar for peers on the team by generating excellent code, driving high-signal code review processes, and sharing technical knowledge.

Requirements & Tech Stack

• Solid, hands-on experience with large language models — including practical fluency with LLM APIs, prompt engineering, context window management, retrieval-augmented generation, and the operational realities of running LLM-backed systems.
• Experience building and shipping agentic systems: tool use, multi-step reasoning, agent orchestration frameworks, memory and context persistence.
• Hands-on experience with AI-assisted engineering tools — Claude Code, Codex, Cursor, or similar — and a track record of integrating these into real development workflows.
• Full-stack engineering depth sufficient to contribute across the agent's entire surface area — including backend services, client SDKs, and platform-specific integration patterns.
• Strong engineering craft: readable, well-structured, production-quality code; opinionated views on testing, local dev ergonomics, and scaffolding.
• Clear communication skills — able to discuss technical tradeoffs, flag issues early, and collaborate effectively across disciplines.
• Comfort operating in a fast-moving, ambiguous environment where models, frameworks, and user expectations are rapidly evolving.
• Experience collaborating cross-functionally with product, design, platform, and security teams in the context of shipping user-facing AI products.
• Familiarity with the quality, trust, and reliability requirements of shipping AI features to a large consumer and enterprise audience, including responsible AI considerations specific to generative and agentic systems.

Qualifications

• Details regarding specific years of experience are not explicitly stated in the provided text.