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.

Machine Learning Engineer & Architect for Adobe Journey Optimizer B2B, focusing on AI and Agents team to define and own ML architecture vision for B2B journey orchestration platform. Role involves training/finetuning models, architecting ML pipelines, recommending models/metrics/governance, providing technical leadership, and deploying/operating ML systems. Requires 10+ years ML experience, 3+ years generative AI, strong Python, deep learning engineering, and experience with post-training techniques.

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.

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.

This role focuses on engineering GenAI backend services for video, deploying ML models from experimentation to production, optimizing performance, and enhancing MLOps workflows. It requires expertise in Generative Video AI, model optimization, inference efficiency, and GPU acceleration for cloud-scale products.

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.

Senior Machine Learning Engineer to build and implement the AI framework for Adobe Express, focusing on Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI. This role involves developing and operationalizing end-to-end systems, including LLM orchestration, inference, data pipelines, and evaluation frameworks, with a strong emphasis on distributed systems and large-scale service development.

Forward Deployed AI Engineer responsible for the end-to-end development and launch of GenAI applications using Adobe and third-party generative models. This role involves embedding into customer teams to rapidly prototype, engineer full-stack applications, and bridge field-proven use cases back to the product roadmap. The engineer will also focus on automation, scaling, and documenting best practices.

Senior Engineering Manager to lead teams building and evolving the Adobe Firefly AI Platform, focusing on large-scale model training, fine-tuning, inference, and serving infrastructure for generative AI products. The role involves technical leadership, architectural decisions, and team management to ensure cost efficiency, performance, and reliability.

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.

Software Engineer role focused on building and deploying end-to-end GenAI applications for enterprise customers. The role involves prototyping, productionizing, and owning the full lifecycle of GenAI solutions, embedding with customers, and contributing to a platform of reusable components. Requires strong full-stack development, hands-on GenAI experience (LLMs, RAG, embeddings, agent frameworks), cloud/DevOps fluency, and customer-facing communication skills.

Senior Software Engineer role focused on architecting and deploying production-grade AI systems, specifically Agentic AI workflows and RAG pipelines. Responsibilities include system architecture, GenAI implementation, model optimization (fine-tuning, prompt engineering), API development, and MLOps. Requires advanced Python, AI frameworks, vector databases, cloud platforms, data engineering, and DevOps skills.

Technical Architect for Adobe Consulting's Brand Concierge Solution, a NextGen Conversational Agent. This hands-on role involves designing, building, and deploying production-grade agentic AI systems, owning end-to-end solution architecture, and leading delivery teams. Responsibilities include prototyping, code review, selecting LLMs and embedding strategies, and managing non-functional requirements like latency and cost optimization.

This role focuses on designing and building AI agents that automate and augment end-to-end workflows, transforming creative and enterprise processes. The engineer will translate business problems into AI-driven solutions, develop ROI models, and prototype/iterate with users, partnering across teams to scale solutions. Experience building AI agents, copilots, or LLM-powered systems, strong systems thinking, and a commercial mindset are key requirements.

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.

Senior Forward Deployed Engineer role focused on implementing and integrating AI capabilities (specifically LLM-based applications) into customer workflows and applications. This involves building A2A integration patterns, creating SDKs, analyzing model behavior in production, designing evaluation pipelines with metrics and guardrails, instrumenting AI features with observability, and designing/implementing AI-backed services. The role acts as a bridge between customer needs and internal product/engineering, ensuring AI features are usable, measurable, and scalable.

Manager for a team building core systems that support training and development of foundation models for generative AI (image, video, multimodal). Focus on foundational training frameworks, tooling, and codebases for large-scale experimentation, reliable execution, and rapid iteration. Requires strong software engineering, systems experience, and applied ML understanding.

Lead Forward Deployed Engineer at Adobe, focusing on integrating AI capabilities into customer applications and workflows. This role involves implementing A2A integration patterns, creating reusable SDKs, analyzing model behavior in production, designing evaluation pipelines, and instrumenting AI features with observability. The engineer will also design and implement AI-backed services using Python and PyTorch, and act as a bridge between customer needs and internal product/engineering teams to ensure AI features are usable, measurable, and scalable.

Principal Service Engineer for Adobe Firefly's Generative AI Services team, leading the development and scaling of GenAI services and APIs. This role involves designing inference infrastructure, providing technical leadership, evaluating MLOps technologies, and driving cross-functional alignment for enterprise-scale GenAI systems powering various Adobe products.

Staff Software Engineer focused on building and scaling the AI/ML platform for Adobe Experience Platform's Personalization ML solutions and Generative AI capabilities. The role involves MLOps, infrastructure, and reliability engineering for scalable model training, reliable inference, automated ML workflows, and production-grade AI systems.

Senior Software Development Engineer at Adobe Express focused on building scalable, reliable, and performant applications. The role involves end-to-end system design and architecture, with a specific emphasis on designing and developing agentic workflows and systems that leverage generative AI/LLMs to automate tasks and enhance user productivity. Collaboration with cross-functional teams, mentoring engineers, rapid prototyping of AI features, and partnering with Product Management on AI capabilities are key responsibilities. The role requires proficiency in AI toolsets like agents, MCP, and RAG, and experience with AI evaluation strategies.

Machine Learning Data Engineer at Adobe focused on building foundational infrastructure for large-scale multimodal AI training and inference. The role involves developing distributed data loaders, feature enrichment pipelines, and dataset management systems to support foundation model training at petabyte scale, processing billions of multimodal assets.

Internship role focused on building and implementing evaluation frameworks for AI Assistant quality, including automated pipelines using LLM-as-a-judge and classical ML models, and analyzing user interaction data to understand AI performance and failure modes. The role involves working with AI-powered product assistants within Adobe Experience Platform.

This role focuses on developing and deploying low-latency, high-performance distributed ML services and systems for Adobe Document Cloud Services. The engineer will be responsible for the end-to-end lifecycle of these services, serving a large user base globally.

Senior Staff Engineer to lead the Agent Platform for Firefly Boards, an AI-powered creative app. This role owns the production-grade engineering systems for the server-side agent runtime, integration with the central agent platform, and the application stack enabling real-time agent actions on an infinite canvas. Responsibilities include state management, checkpointing, error recovery, observability for long-running operations, defining the browser/server execution boundary for agent tools, and integrating with Adobe's central agent platform. The role also involves refactoring APIs for agent consumption and ensuring production-grade systems concerns like observability and latency budgets. This is a senior IC role focused on engineering direction and cross-organizational partnerships.

Engineering Manager (AI/ML) at Adobe leading a team focused on building next-generation AI-enabled audio & video editing solutions. The role involves people management, technical strategy, and hands-on experience integrating AI/ML into production software for consumer-facing desktop applications.

Internship role focused on applying AI/ML techniques to power next-generation marketing, personalization, and decisioning systems. The role involves building, scaling, and deploying ML systems, including autonomous agents and agentic workflows, and contributing to real-world AI products used by millions. Emphasis on end-to-end lifecycle ownership and operationalizing ML/GenAI.

Software Development Engineer to join a generative AI team, focusing on building generative AI powered tools and AI Agents. The role involves crafting web experiences, promoting design thinking, and using product-driven development for rapid iteration.

Internship role focused on building AI assistants and multi-agent systems for enterprise software, involving research, algorithm development, and evaluation.

Software Development Engineer 5 at Adobe to pioneer semantic enrichment within the Adobe Experience Data Model (XDM), transforming how businesses understand and act on their data by integrating semantic search, knowledge graphs, and advanced natural language understanding (NLU). The role involves crafting intelligent search solutions that incorporate NLU, machine learning, and knowledge graphs to deliver relevant insights, enabling brands to quickly access, understand, and act upon data.

Senior Infrastructure Developer to own, evolve, and scale the platform powering demanding ML training and serving workloads. This role involves architecting Kubernetes-native systems, leading cross-geo projects, writing production-grade code (Go, Python, Rust), and ensuring the reliability and efficiency of large-scale GPU clusters. Focus on infrastructure as code, deep observability, and complex networking challenges within a multi-cloud environment.

Senior DevOps Engineer specializing in AI Ops to own infrastructure provisioning, CI/CD automation, telemetry pipelines, and production deployment for AI-powered services, agents, and orchestration systems. The role focuses on building and operating infrastructure for reliable, observable, and scalable AI systems in production, with SRE responsibilities for ensuring reliability, resilience, scalability, security, and cost-effectiveness.

Senior Engineering Manager at Adobe to lead a high-performing engineering team in developing next-generation multi-cloud services, focusing on AI-powered features for customers and internal productivity. The role involves technical leadership, product architecture, roadmap planning, and talent acquisition within the Digital Experience business unit.

Seeking a Principal Architect to lead the architecture of AI-enabled customer experience platforms, focusing on integrating AI capabilities like RAG, GenAI, and agentic automation into support and sales processes. The role involves defining reference architectures, guardrails, and ensuring alignment across multiple initiatives and teams, with a vendor-agnostic approach.

This role focuses on architecting and designing enterprise solutions that leverage generative and agentic AI, specifically Adobe's Firefly Enterprise Solutions. The architect will lead technical discovery, design scalable solutions integrating AI into customer workflows, build prototypes, and create technical roadmaps. The role also involves developing reusable assets, collaborating with product teams, and staying at the forefront of AI trends to advise customers and shape Adobe's technical positioning. The primary focus is on applying AI to enterprise workflows and content creation at scale.

Machine Learning Engineer at Adobe Express AI Foundations to build and scale the core AI platform powering creativity across design, imaging, motion, and personalization. The role involves developing production systems for Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI, focusing on model integration, inference services, data pipelines, storage, caching, analytics, and evaluation tooling.

Backend engineer to enable and accelerate Video APIs powered by machine learning models. Will work closely with ML researchers, bringing AI experiences to users by enabling large-scale productization through cloud-based services. Design and development of services/components, full lifecycle responsibility, collaborate with ML engineers on orchestration and inference workflows, build scalable cloud services with observability, build GPU-optimized model pipelines, work with distributed teams to build GenAI services/API for video workflows, partner with internal client teams and enterprise customers.

This role focuses on building Gen AI-powered concierge experiences for enterprise customers, involving scalable distributed systems, LLMs, RAG, and agentic workflows within Adobe Experience Cloud.

Software Engineer to develop, build, and scale core GenAI services, evaluation frameworks, and agentic capabilities. This role focuses on building shared GenAI core services (Voice, Evaluation, Moderation, AI-powered bug triage) and enabling world-ready GenAI features and agents by embedding internationalization and global quality requirements. The role also involves supporting the modernization and stability of the Continuous Localization (CL) platform and developing CL workflows for LLM-based development.

Senior Technical Consultant for Adobe Workfront, focusing on designing and implementing AI-driven automation and content supply chain solutions for enterprise customers. The role involves integrating Workfront with other enterprise systems, architecting AI-augmented workflows using agentic frameworks, and guiding clients through complex integration needs.

Senior Software Engineer to design, build, and scale core GenAI services, evaluation frameworks, and agentic capabilities for Adobe's Experience Cloud. The role involves GenAI platform engineering, developer enablement, and global readiness, with ownership of architecture and cross-team impact.

This role is for a Computer Scientist 2 (Frontend) at Adobe, focusing on building new features and experiences for Adobe Express. The role involves full-stack development, including front-end (JavaScript, TypeScript, React), back-end (NodeJS, APIs), and cloud services (AWS). A significant part of the role involves integrating AI capabilities into product features and building agentic workflows for the SDLC, requiring careful design for safety, reliability, and performance.

Director of Engineering for Adobe's Graph platform, a node-based creative system powering generative AI workflows and multimodal media pipelines. The role involves leading the engineering team to build both a creator-facing application and a platform layer, including the execution engine, stateful workflow composition, and integration of GenAI models.

Full Stack Engineer with expertise in TypeScript, JavaScript, and Web Component Frameworks, responsible for end-to-end feature development, system design, and integrating AI capabilities into product experiences, specifically focusing on building multistage LLM pipelines and AI-powered content generation systems.

Full stack engineer for Adobe's Firefly Boards team, focusing on building and scaling an AI-powered mood-boarding and ideation app that leverages multi-modal LLMs to provide a non-linear canvas for creative professionals. The role involves developing innovative user experiences and integrating generative AI capabilities.

Senior Software Engineer for Adobe Express Motion AI team, focusing on building and optimizing scalable software systems for AI features in motion, video, and animation workflows. The role involves integrating generative AI and temporal models into the Adobe Express platform, tackling complex technical challenges in media generation and processing, and collaborating with cross-functional teams to deliver user-facing AI-powered creative tools.

Senior Backend Engineer focused on the inference service for Adobe's Firefly generative AI models. The role involves designing, leading, and optimizing backend services for high performance, latency, and load, with a focus on GPU-based ML inference.

Senior AI Platform Engineer focused on building the foundational infrastructure for AI, analytics, and autonomous agents at scale. The role involves designing and building streaming-first data pipelines, extending the ML Attribute Store with low-latency serving, developing Agent Data APIs and tool servers for autonomous AI agents, and creating an agentic framework for automation and self-healing pipelines. Experience with LLM integration, agentic AI frameworks, and cloud platforms is required.