Currently tracking 218 active AI roles, down 50% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $114k–$397k (avg $221k).
Adobe has 306 active job listings related to artificial intelligence. The majority of these roles, 47%, are focused on agents, with application-focused roles making up another 25%. Engineering is the primary function for these positions, with the United States being the dominant hiring country. Frequent technical tags include model serving, agent orchestration, and fine-tuning, suggesting a focus on deploying and managing AI models.
Adobe currently has 314 active AI-related roles in our index. The most common open titles are: Senior Software Development Engineer (12), Machine Learning Engineer (6), Machine Learning Engineer 4 (5), Principal Product Manager (5), Software Development Engineer (5). Most positions are in Engineering and Product.
Adobe's active AI hiring is concentrated in: agents (48%), application (25%), serving infrastructure (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Adobe is hiring AI talent in: United States (236 roles), India (50 roles), Romania (22 roles), Canada (3 roles).
Job postings at Adobe most frequently reference: model serving, agent orchestration, llm observability, fine tuning, inference infra.
In the past 30 days, Adobe has posted 119 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer 5 Machine Learning Engineer to build and ship LLM-powered systems simulating consumer audiences for pre-testing ads and content. Develops inference and reasoning harnesses on LLMs, fine-tunes LLMs on data, and builds evaluation datasets and benchmarks. Requires substantial hands-on experience with LLM applications in production, including agentic systems, fine-tuning, and RLHF/RLAIF. Experience with MLOps and cloud ML services is needed. The role focuses on bringing cutting-edge AI research in synthetic audiences into a production product. | AgentPost-train | 9 |
| Machine Learning Engineer 5 Machine Learning Engineer to build and ship LLM-powered systems simulating consumer audiences for pre-testing ads and content. Develops inference and reasoning harnesses on LLMs, fine-tunes LLMs on data, and builds evaluation datasets and benchmarks. Requires substantial hands-on experience with LLM applications in production, including agentic systems, fine-tuning, and RLHF/RLAIF. Experience with MLOps and cloud ML services is needed. The role focuses on bringing cutting-edge AI research in synthetic audiences into a production product. |
| AgentPost-train |
| 9 |
| Principal Scientist - Agentic Product Principal Scientist to lead the end-to-end technical architecture and production buildout of Adobe's Agentic Product, focusing on LLM integration, agentic reasoning, and full-stack delivery across platforms. The role involves driving hands-on implementation, championing AI-assisted engineering practices, and collaborating across teams to ensure quality, reliability, and responsible AI. | AgentServe | 9 |
| Director, ML Engineering Director, ML Engineering for Adobe's Firefly Foundry, an enterprise managed-service for custom multimedia generative AI. This role owns the engineering function for model productionization, serving, and operation at enterprise scale, focusing on inference, cost-to-serve, tenancy, and self-serve capabilities. The role involves leading a multi-team engineering organization, defining technical strategy for training and inference, and ensuring production reliability and economics. | ServePost-train | 9 |
| Senior Machine Learning Engineer, Firefly Foundry ML infra engineer to build and optimize infrastructures for large foundation model training on thousands of GPUs, including data processing, PyTorch training, and GPU optimizations with custom CUDA kernels. Focus on generative AI for text, images, and videos. | DataServe | 9 |
| Director, Engineering – Agentic Product Director of Engineering for Adobe's Agentic Product, focusing on leading the technical execution of an AI-native experience for creators. The role involves defining, building, and shipping agentic experiences, ensuring end-to-end product quality, and growing the engineering team. Requires strong experience in AI/ML product engineering, LLM APIs, agent frameworks, and shipping user-facing AI products at scale. | Agent | 9 |
| Sr Staff Machine Learning Engineer, Adobe Firefly Services Senior Staff Machine Learning Engineer at Adobe focused on building and optimizing scalable, high-performance generative AI services and inference pipelines for integration into Adobe products. The role involves designing GenAI services, APIs, and ML workflows for model customization and serving, with a strong emphasis on GPU-accelerated training and inference optimization. | ServePost-train | 9 |
| Sr Machine Learning Engineer 5 -- AEP, Agentic System Senior Machine Learning Engineer to build and operate scalable intelligent AI systems for end-user AI products, focusing on agentic systems including orchestration, tool integration, retrieval, memory, evaluation, safety/guardrails, and high-performance backend systems. The role involves end-to-end architecture ownership, building AI-powered product capabilities, designing agent orchestration, developing core platform components (RAG, memory), establishing safety/governance/MLOps, and providing technical leadership. | Agent | 9 |
| Technical Architect - Agentic Systems & Assistant Platforms Technical Architect role focused on designing and architecting advanced assistant and agentic frameworks using LLMs, VLLMs, and MLLMs, with a specific emphasis on image and multimedia domains. The role involves overseeing technical strategy, collaborating with cross-functional teams, mentoring engineers, and transforming conceptual designs into production-ready solutions. Key responsibilities include defining the vision and roadmap for agent orchestration, tool usage, memory, and scalable evaluation. | Agent | 9 |
| Senior Staff Applied Scientist - AI/ML Senior Staff Applied Scientist role at Adobe focusing on transforming AI/ML research breakthroughs into innovative product features for Generative AI, LLMs, and multimodal AI. The role involves scouting, adapting, and improvising research, prototyping, rapid experimentation, and deploying practical innovations for Adobe's products. Responsibilities include developing and enhancing GPU-accelerated pipelines for model training and inference, collaborating with researchers and ML engineers, and publishing work. Requires a Ph.D. or Masters with 10+ years of experience in AI/ML, with expertise in training AI/ML models in multimodal LLMs, Image, or Video, proficiency in training and optimizing large-scale models, and experience with post-training techniques like fine-tuning and alignment. | Post-trainServe | 9 |
| Machine Learning Engineer Machine Learning Engineer at Adobe to build advanced AI platform for creative workflows, focusing on reasoning systems, tool orchestration, and multimodal integrations using LLMs and VLLMs. The role involves post-training and evaluation of LLMs, designing and implementing agent system architectures, and developing practical agents for image generation and editing within flagship products like Photoshop and Lightroom. | AgentPost-train | 9 |
| Principal Architect, Express AI Foundations Principal Architect to build and implement the AI framework for Adobe Express, merging strong ML skills with proficiency in distributed systems, data architecture, and large-scale service development. This role blends applied research and engineering leadership, focusing on Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI, spanning model orchestration, inference systems, data pipelines, caching and storage layers, session analytics, and continuous evaluation frameworks. | AgentServe | 9 |
| Chief Architect for Adobe Intelligence Platform Seeking a Sr. Principal Architect to lead the design, build, and evolution of the Adobe Intelligence Platform, an AI infrastructure enabling agentic experiences across Adobe products. The role involves hands-on technical leadership, defining system boundaries, and driving execution for a platform encompassing agentic orchestration, model gateways, knowledge graphs, and planning/reasoning layers at enterprise scale. | AgentServe | 9 |
| Forward-Deployed AI Engineer - Marketing Analytics & Data Science This role focuses on embedding AI engineers within marketing teams to build tools and automations, transforming workflows with agentic AI at the center. The engineer will prototype solutions, gather feedback, and share learnings across the organization, measuring success by improved user workflows. | Agent | 8 |
| Forward Deployed AI Engineer — Lifecycle Marketing This role focuses on building and deploying AI agentic systems to reinvent marketing workflows within Adobe's Growth Marketing & Insights organization. The engineer will be embedded with the Lifecycle Marketing team, redesigning repeatable workflows and creating tools to transform how marketing managers operate. The goal is to improve existing processes and measure success by the impact on user workflows. | Agent | 8 |
| Forward-Deployed AI Engineer This role is for a Forward-Deployed AI Engineer embedded within a marketing team to rebuild workflows with agentic AI at the center. The engineer will build tools and automations, prototype solutions, and share learnings to scale good ideas across the organization, ultimately aiming to improve how people work. | Agent | 8 |
| Machine Learning Engineer Machine Learning Engineer to build AI systems for Adobe Journey Optimizer's autonomous operating system, focusing on improving product quality, accelerating issue resolution, and enhancing customer experience through intelligent automation and continuous learning. The role involves building LLM-based workflows, knowledge systems using vector embeddings, and integrating AI capabilities with production infrastructure. | Agent | 8 |
| Engineering Manager, Express AI Foundations Engineering Manager to lead a team building the AI infrastructure for Adobe Express, focusing on Agentic AI, Imaging AI, Motion AI, and Personalization AI. The role involves technical leadership, people management, and owning the delivery of the AI stack including LLM orchestration, inference services, data pipelines, and evaluation frameworks. | ServeAgent | 8 |
| Sr. Machine Learning Engineer 4 Senior Machine Learning Engineer at Adobe focused on designing, building, and optimizing backend services for ML and GenAI features, including agentic systems. The role involves end-to-end ownership from concept to production, model evaluation, and operationalization, with a strong emphasis on shipping customer-facing features. | AgentServe | 8 |
| Senior Full Stack Engineer – Agentic Product Senior Full Stack Engineer to build an AI-native agentic product across the full stack, integrating LLMs, agentic reasoning, and production infrastructure for Adobe's creative platforms. The role involves hands-on implementation, championing AI-assisted engineering practices, and collaborating across teams to ensure quality and scalability. | AgentServe | 8 |
| Machine Learning Engineer -4 – Agentic AI & Personalization Machine Learning Engineer focused on building agentic AI systems for enterprise personalization, involving LLM-powered agents, recommendation systems, and end-to-end ML pipeline architecture including low-latency inference and MLOps. | AgentServe | 8 |
| Senior Engineering Manager – Agentic Product Lead a team of engineers building Adobe's Agentic Product, an AI-native experience integrating generative models and creative intelligence for creators. This hands-on leadership role involves daily execution, team growth, and shipping quality agentic experiences across Adobe's surfaces, partnering with Product Management and collaborating with platform teams. | Agent | 8 |
| Senior Software Development Engineer, Agent Workflows, Firefly Boards Senior Software Development Engineer to own the workflow layer for Firefly Boards' agentic capabilities. This role focuses on building and managing the agent workflows, including safety, quality, and cost controls, and ensuring survivability across interruptions. The primary focus is on the application layer that runs on top of the agent platform. | Agent | 8 |
| Researcher/ML Engineer This role focuses on developing and deploying AI and computer vision technologies for Adobe's imaging products, including a new experimental camera app. Responsibilities include researching, developing, and optimizing algorithms, and translating them into production-ready code for various platforms. | ShipPost-train | 8 |
| Sr Machine Learning Engineer, Adobe Firefly Services Senior Machine Learning Engineer focused on building and optimizing scalable generative AI services and inference pipelines for Adobe's creative products. The role involves designing core GenAI services, APIs, and ML workflows for model customization, serving, and integration, with a strong emphasis on GPU-accelerated training and inference optimization. | ServePost-train | 8 |
| Sr Engineering Manager, AI Enablement Senior Engineering Manager to lead a team building a central AI Platform focused on Agentic AI, MCP, and A2A frameworks. The role involves partnering with Product and Business leaders, building reusable AI capabilities, establishing standards, and leading a high-performing AI engineering team. Requires 10+ years of experience, including platform team leadership and experience with Generative AI platforms, Agentic AI systems, LLMs, RAG, and prompt orchestration. | Agent | 8 |
| Principal Engineer AI/ML Principal Engineer AI/ML at Adobe, focusing on designing, building, and scaling AI/ML systems for GenStudio. The role involves framing product features as ML tasks, analyzing trade-offs, managing data, implementing research techniques, defining benchmarks, architecting scalable ML systems, and optimizing model deployment. Requires strong software engineering and ML/DL expertise, with experience in Python, PyTorch, and GPU/TPU environments. | ShipAgent | 8 |
| Senior / AI Agent Engineer, Brand Concierge Senior AI Agent Engineer role focused on designing, building, and maintaining intelligent agents for enterprise use cases like customer experience, discovery, support, and lead qualification. Responsibilities include agent development, multi-agent communication, workflow orchestration, lifecycle management, continuous improvement, and deployment. Requires experience with LLM frameworks, conversational agents in production, and cloud platforms. | Agent | 8 |
| Machine Learning Engineer 4 Senior Machine Learning Engineer to design, build, and scale agentic AI platforms and products for enterprise customer experiences and marketing campaigns, focusing on the AEP Agent Orchestrator. | AgentServe | 8 |
| Staff AI VFX Engineer Staff AI VFX Engineer at Adobe's Firefly Foundry, focused on integrating generative AI into high-end visual effects for feature films and episodic content. The role involves building and validating AI-driven VFX workflows, solving production challenges like temporal coherence and art-directable control, owning the integration surface with DCC tools (Nuke, Houdini, Maya, etc.), and implementing multi-modal model orchestration for image, video, animation, and 3D generation models. Requires deep fluency in VFX workflows and working knowledge of generative AI fundamentals, with a focus on shipping production-grade AI-driven assets. | AgentPost-train | 8 |
| Sr. AI Systems Architect (AI/ML), Brand Concierge Senior AI Systems Architect role focused on designing and architecting agent-based workflows, data pipelines, and orchestration systems for enterprise applications. This involves translating business needs into scalable AI solutions, defining RAG architecture, authoring technical specifications for LLM-based solutions, and collaborating with ML engineers and product teams. | Agent | 8 |
| Machine Learning Engineer, Firefly Services This role focuses on building and optimizing scalable, high-performance generative AI systems, specifically for inference pipelines and integration into Adobe products. It involves designing and building ML workflows for model customization, serving, and ecosystem integration, with a strong emphasis on GPU-accelerated training and inference. | ServePost-train | 8 |
| Senior Data Science Engineer, GenAI Platforms & Data Infrastructure Senior Data Science Engineer role focused on building and operating production data and AI infrastructure for Adobe's Digital Experience business. The role involves creating LLM-powered agents, customer intelligence products, and reusable platform services, with a strong emphasis on data pipelines, feature workflows, and system reliability. The ideal candidate has deep data engineering experience, GenAI fluency, and platform thinking to ship reliable AI-enabled workflows into production. | AgentData | 8 |
| Machine Learning Engineer Machine Learning Engineer at Adobe focused on designing, building, and optimizing backend services for ML and GenAI features, including agentic systems and orchestration. The role involves developing, evaluating, and deploying ML models, taking features from 0 to 1, and integrating solutions into production workflows. Requires strong Python software engineering, experience with production ML systems, and familiarity with cloud platforms. | AgentServe | 8 |
| Machine Learning Architect 5 - GenAI Experiences This role is for a Senior Machine Learning Architect focused on building and shipping AI-powered user experiences within Adobe Experience Cloud. The architect will design and evolve ML systems that blend GenAI and classical ML techniques, focusing on user-centric data, inference pipelines, and evaluation through user behavior. Responsibilities include end-to-end ownership from data to production, defining evaluation frameworks, and driving system reliability and scalability. | AgentServe | 8 |
| Senior Machine Learning Engineer Senior Machine Learning Engineer at Adobe Journey Optimizer B2B, focusing on AI-powered customer journey orchestration. The role involves training and fine-tuning ML models, architecting ML pipelines, and contributing to the deployment and production operations of ML models and systems. Experience with generative AI, LLMs, fine-tuning, and MLOps is required, with a preference for RAG, agentic workflows, and personalization use cases. | Post-trainAgent | 8 |
| Sr. Applied Scientist Sr. Applied Scientist at Adobe focused on improving the quality and controllability of generative multimodal models, specifically in mid-training capabilities for image and video editing. The role involves designing and implementing training pipelines, identifying quality gaps, developing data curation and distributed training workflows, and optimizing inference for production environments. | Post-trainData | 8 |
| Senior AI Platform Engineer Senior engineer to design and build next-generation AI systems for Adobe Express, focusing on scalable, production-grade AI platforms with agentic experiences. This role involves architecting end-to-end systems for model orchestration, tool integration, memory, inference, data flows, and evaluation. | AgentServe | 8 |
| Senior AI Engineer Senior AI Engineer at Adobe responsible for building and deploying end-to-end AI products, including GenAI applications, LLM-powered agents, and RAG systems. The role involves full lifecycle ownership from ideation with stakeholders to deployment and impact measurement, leveraging AI-assisted coding tools for rapid development on cloud infrastructure. | Agent | 8 |
| Machine Learning Engineer, Adobe Firefly Services Machine Learning Engineer focused on building and optimizing scalable generative AI services and inference pipelines for Adobe products. The role involves integrating various generative models, optimizing them for performance, and building APIs for product integration. | ServePost-train | 8 |
| Sr Machine Learning Engineer- ML Infrastructure & Data Platforms Senior Machine Learning Engineer focused on building infrastructure for large-scale, multimodal AI training and inference. The role involves developing distributed data loaders, data pipelines, batch inference systems, and improving system performance, scalability, and reliability. It also includes implementing search and retrieval systems, CI/CD workflows, and partnering with researchers to turn model requirements into scalable systems. | ServeData | 8 |
| Senior Machine Learning Engineer, AI Platform Senior Machine Learning Engineer focused on building and implementing AI platforms, leveraging deep learning technologies, and working with large-scale computing frameworks to analyze and leverage data for digital experiences. | Serve | 8 |
| Machine Learning Engineer Machine Learning Engineer to optimize customer experience orchestration by building products that transform audience creation, journey optimization, and personalization. Focus on developing innovative models, designing and deploying applications with predictive and generative models, building autonomous agents, and implementing ML-Ops best practices. | AgentServe | 8 |
| Director of Engineering – Machine Learning & AI Products Director of Engineering role focused on leading the development and end-to-end delivery of AI-native, production-ready machine learning products for external clients. Responsibilities include technical and product leadership, team scaling and management, and ensuring excellence in production operations. Requires extensive experience in delivering and managing AI/ML products in production, with strong business and commercial exposure. | Ship | 8 |
| Sr Manager, Machine Learning Engineering, Firefly Services Senior Manager, Machine Learning Engineering for Adobe Firefly's GenAI Product Services team. The role involves leading a team to build, deploy, optimize, and scale generative models and APIs for enterprise customers. Responsibilities include technical leadership, strategy definition, roadmap shaping, and cross-functional collaboration. The ideal candidate has strong experience in generative AI, production-scale ML deployments, and engineering leadership. | ShipServe | 8 |
| Machine Learning Engineer 3 Machine Learning Engineer at Adobe to optimize customer experience through predictive and generative models, focusing on autonomous agents and agentic frameworks. The role involves designing, developing, and deploying applications, implementing ML-Ops, and collaborating with research and product teams. | AgentPost-train | 8 |
| Applied Scientist Applied Scientist at Adobe focused on transforming research breakthroughs in Generative AI, LLMs, and multimodal AI into innovative product features for millions of users. The role involves scouting, adapting, and improvising the latest research, prototyping, and deploying practical innovations, with a strong emphasis on training and optimizing large-scale models, including post-training techniques and GPU-accelerated pipelines for both training and inference. | Post-trainServe | 8 |
| Senior Customer Facing Applied AI Engineer Senior Customer Facing Applied AI Engineer at Adobe, focused on implementing AI capabilities into customer applications and workflows, analyzing model behavior in production, designing evaluation pipelines, and ensuring AI features are usable, measurable, and scalable. The role involves deep technical work and on-site customer collaboration. | AgentEval Gate | 8 |
| 2026 University Graduate - Machine Learning Engineer Machine Learning Engineer role focused on building and optimizing scalable, high-performance generative AI inference pipelines and APIs for integration into Adobe's consumer products. The role involves optimizing models for latency and throughput, productionizing generative models, and developing enterprise-scale systems for customization and serving. | ServePost-train | 8 |
| Director of Software Engineering & Applied AI (Level 6) – Product Success Engineering, Adobe Experience Platform Director of Software Engineering & Applied AI to lead the development of AI agents, tooling, and automation for customer support, operation, and scaling of Adobe Experience Platform (AEP). Focuses on agentic-first solutions for troubleshooting, proactive monitoring, and adoption acceleration, transforming reactive support into proactive, data-driven customer success operations. | Agent | 8 |