Senior Full Stack Engineer – Agentic Product

Adobe•San Jose, CA

10d•Hybrid

About The Position

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. This role involves bringing generative models, creative intelligence, and Adobe's capabilities together for hundreds of millions of creators. You will own the hands-on buildout of the agent across the full stack and across Adobe's target platforms (desktop, mobile, web, and embedded surfaces). This is an opportunity to build the engineering foundations of Adobe's next major AI product, from model integration and agentic reasoning patterns to production infrastructure and cross-platform delivery. The ideal candidate has deep, hands-on full-stack expertise, proven experience shipping agentic systems, enthusiasm for transforming engineering with AI tools, and the craft to write production-quality code.

Requirements

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 in production.
Experience building and shipping agentic systems: tool use, multi-step reasoning, agent orchestration frameworks, memory and context persistence, and the failure modes that emerge at each layer.
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.
Enthusiasm for pushing the boundary of what AI-augmented engineering can look like at the frontier.
Full-stack engineering depth sufficient to contribute across the agent's entire surface area — including backend services, client SDKs, and platform-specific integration patterns for Adobe's target platforms.
Strong engineering craft: readable, well-structured, production-quality code; opinionated views on testing, local dev ergonomics, and the scaffolding that helps a team stay productive as a codebase grows.
Clear communication skills — able to discuss technical tradeoffs with PM leads and senior technical stakeholders, flag issues early, and collaborate effectively across disciplines.
Comfort operating in a fast-moving, ambiguous environment where the underlying models, frameworks, and user expectations are all rapidly evolving — strong enough foundations to move fast without building on sand.
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.

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 that meet Adobe's quality and reliability bar for a large, diverse audience.
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, raise code quality, and fundamentally change how the team ships.
Model new workflows where AI is a first-class collaborator in the development process.
Contribute to developer experience: tooling, local development loops, CI/CD ergonomics, and the scaffolding that lets a team move fast and confidently in a fast-moving AI product environment.
Stay current with the model capabilities ecosystem, evaluating new LLM approaches and frameworks, and contributing recommendations on when and how to adopt them.
Help build and maintain the evaluation and quality framework for agent behavior — the evals, benchmarks, and systematic feedback loops that allow the team to measure progress and catch regressions as capabilities evolve.
Partner with Engineering and Product leadership to translate product ambitions into technically grounded delivery — surfacing constraints early, proposing implementation options, and ensuring scope is set based on accurate technical understanding.
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 the operational requirements of a product at Adobe's scale.
Raise the bar for peers on the team by generating excellent code, driving high-signal code review processes, and sharing technical knowledge in agentic engineering.