Adobe

Technical Program Manager

• Develop change strategies and roadmaps aligned with business objectives
• Conduct customer analyses and deliver change impact assessments
• Build relationships with executive sponsors and business leaders
• Build coordinated communications strategies to foster awareness and adoption of tools, processes, and policies
• Partner with Line of Business leaders, Field Readiness & Enablement teams, and Product Managers to define adoption and enablement strategies
• Measure readiness and adoption, reinforcing new behaviors and ways of working
• Drive AI adoption efforts to support business outcomes

Program Manager – IT

Data Engineer

• Own end-to-end designs shaping the Security Data Platform architecture on Databricks and AWS using Spark, Delta Lake, and Unity Catalog
• Translate ambiguous needs into design proposals, implementation plans, and production capabilities
• Build and evolve distributed batch and streaming pipelines for EDR telemetry, network logs, identity events, cloud audit logs, and other security data sources
• Write and review production Python and SQL code, develop platform features, refactor unreliable code, and establish engineering patterns
• Lead code and design reviews and own test strategy and automation choices
• Build and maintain tested Terraform modules for AWS and Databricks infrastructure, including S3, IAM, VPC networking, and MWAA
• Automate delivery through version control and CI/CD
• Design layered lakehouse data models and normalization patterns, including OCSF mappings where appropriate
• Establish data contracts, quality checks, cataloging, classification, lineage, access controls, and retention policies
• Engineer and operate Airflow and MWAA orchestration, including dependencies, retries, backfills, alerting, and automated recovery
• Define service level objectives and instrument data freshness, completeness, pipeline health, and query performance
• Diagnose and resolve complex production issues across Spark, storage, orchestration, and cloud infrastructure
• Improve incident response, runbooks, recovery testing, and operational readiness
• Lead measurable cost and performance improvements through query and Spark tuning, storage lifecycle policies, partitioning, and compute right-sizing
• Lead cross-team technical discussions and communicate decisions, risks, and business impact
• Partner with detection and security analytics engineers on SIEM modernization and automated detection deployment
• Mentor engineers through pairing, technical reviews, documentation, and knowledge sharing
• Evaluate and introduce platform innovations, including AI-assisted engineering and operational automation

Staff Security Data Engineer

Designer

• Create high-quality design across campaigns, multi-platform design, product storytelling, and live experiences
• Develop work from early concept and visual exploration through design development and final execution
• Apply exceptional craft across typography, image-making, layout, composition, and art direction
• Adapt ideas across channels and formats while preserving visual impact
• Create connected, recognizably Adobe work that remains fresh, distinctive, and culturally relevant
• Partner with Creative Directors, Design Directors, Art Directors, Copywriters, Strategists, and Product partners
• Translate campaign and creative ideas into visual territories, creative systems, art direction, and design expression
• Create mood boards, prototypes, and design studies
• Build modular frameworks, templates, and reusable design tools
• Test design ideas across channels, formats, and audience needs
• Use Creative Cloud, Firefly, and emerging generative tools in concepting, prototyping, and production
• Apply responsible AI practices, including provenance, creator rights, and Content Credentials
• Present work, explain design decisions, and respond to feedback
• Partner with Production to carry ideas into execution
• Collaborate with photographers, illustrators, artists, studios, and specialist partners
• Maintain high design standards across fast timelines, multiple workstreams, and changing priorities

Senior Designer

Full-stack Engineer

• Implement Adobe Experience Cloud solutions across Adobe.com and other key Adobe digital surfaces
• Build scalable web data collection and tagging strategies using AEP Data Collection tools, JavaScript, and supporting tools
• Partner with marketing, product, and analytics teams to define tracking requirements and technical specifications
• Design scalable tagging with Adobe Tags and AEP Web SDK
• Build accurate data layers
• Align implementations with XDM schemas and business logic
• Configure AEP schemas, datasets, identity namespaces, and ingestion
• Work with QA to validate implementations using AEP Debugger and browser DevTools
• Uphold data governance and privacy requirements including GDPR and CCPA
• Integrate Martech and third-party tools
• Provide documentation, training, and support on digital data instrumentation standards

Software Development Engineer

Videographer

• Film internal video projects of varying sizes, from individual shoots to larger productions involving external crews
• Develop and maintain the visual appearance and style of Adobe’s video content
• Ensure consistent, high-quality visual standards
• Apply social-first content understanding in framing, pacing, and composition for social platforms
• Occasionally edit quick-turn videos when fast turnaround is needed
• Manage and maintain production equipment, keeping everything organized and shoot-ready
• Partner with in-house producers, editors, art directors, and creative directors from concept through final delivery
• Work on quick-turn shoots typically in San Francisco or Adobe’s San Jose headquarters
• Travel longer distances occasionally throughout the year

Senior Videographer, Social Creative

Machine Learning Engineer

• Apply AI and machine learning techniques to big-data problems
• Build products addressing business problems across the customer lifecycle, from customer analytics to marketing media optimization
• Develop predictive models on large-scale datasets using advanced statistical modeling, machine learning, and analytics techniques
• Develop and implement scalable and efficient modeling algorithms for production systems
• Collaborate with product management and engineering groups to develop new products and features
• Work on projects involving attribution, media mix modeling, budget optimization, personalization, causal analysis, and time series analysis

University Graduate – Machine Learning Engineer

• Design, build, and evolve systems that power Adobe’s products and platforms
• Develop high-quality, reliable, testable, and maintainable code
• Participate in the full software development lifecycle, including design, coding, code review, testing, debugging, deployment, and documentation
• Use modern development tools, including AI-assisted tooling, for coding, testing, debugging, and workflow efficiency
• Improve product quality, performance, scalability, and reliability
• Review and iterate on solutions, identify issues, debug problems, and refine implementations
• Collaborate with engineers, designers, product managers, and other cross-functional partners
• Work independently and collaboratively in a fast-paced development environment
• Learn from the team, seek feedback, and contribute to an inclusive engineering culture
• Perform additional responsibilities as needed based on the specific role or team

Software Engineer, University Graduate

• Ensure the highest level of uptime and Quality of Service for Adobe customers
• Help define service level objectives and service level indicators
• Embed with product teams to develop close collaboration and partnership
• Improve service resiliency through performance/load testing, code review, and Chaos engineering
• Support and maintain globally distributed multi-cloud environments, including AWS and Azure
• Automate repeatable tasks at scale to reduce toil
• Apply AI/ML and generative-AI techniques to reliability engineering, including anomaly detection, predictive alerting, automated root-cause analysis, and log/metric correlation
• Build AI-enabled automation and agents to reduce toil and accelerate incident response
• Solve performance and stability issues using a wide variety of tools
• Participate in an on-call rotation as required
• Determine root causes for production incidents and write high-quality RCA reports
• Mentor junior engineers and share knowledge across teams
• Serve as a technical lead on reliability initiatives when needed
• Promote the DevOps/SRE mentality

Operations

• Drive collaboration with operations leads and key business partners across marketing, finance, and product groups
• Drive business unit alignment and operational efficiency through process improvements, creation, implementation, and execution
• Lead annual and quarterly planning processes in partnership with finance and cross-functional operations partners
• Align teams and identify opportunities to evolve operational processes across the marketing organization and business units
• Drive communication throughout the global marketing organization and partner teams
• Engage and align stakeholders in Adobe’s Creativity & Productivity and Customer Experience Orchestration business units

Marketing Strategy – Operations Director

General

• Lead responses to significant consumer trust incidents involving fraud, abuse, scams, account compromise, and emerging threats
• Coordinate teams across Adobe to assess impact, establish priorities, and drive resolution
• Establish ownership, escalation paths, action tracking, decision-making, and stakeholder communications during incidents
• Partner with Fraud Prevention, Product, Engineering, Customer Support, Legal, Security, GTM, and other teams
• Lead post-incident reviews to identify root causes, policy and control gaps, and prevention opportunities
• Translate incident, investigation, customer experience, and emerging threat insights into consumer trust policies and decision frameworks
• Develop and maintain policies, playbooks, escalation criteria, and operational guidance
• Translate policy into processes, controls, product requirements, training, and customer experiences
• Identify systemic risks and drive consumer protection improvements
• Develop metrics and reporting on incidents, emerging risks, policy effectiveness, and remediation progress

Policy and Incident Specialist

• Develop and build reliable data products, automated pipelines, and reusable interfaces for internal business teams
• Take an end-to-end, full-stack approach spanning data pipelines, APIs, automation, and lightweight application development
• Build automation and intelligent solutions, including RPA workflows and AI/LLM-powered tools
• Maintain engineering ownership and segregation-of-duties controls over SnapLogic, Power Automate, and PowerBuilder platforms
• Translate defined business requirements into technical implementations focused on underlying business problems
• Apply Git-based source control, testing, CI/CD, code reviews, documentation, and monitoring
• Integrate and validate data from internal and external systems, ensuring quality, security, lineage, and governance
• Deliver solutions with measurable business impact tracked through metrics
• Use AI-assisted development tools while validating output quality
• Work embedded with Finance and CAO partners on production-grade data products, automation, and AI-enabled solutions

Data Product Engineer

• Lead the design, development, and deployment of multimodal and generative AI systems spanning vision, language, and other modalities
• Build and productionize transformers, diffusion models, LLMs, and vision-language models for content creation, understanding, and transformation
• Develop agentic AI systems that reason, use tools, interact with models and services, and complete complex multi-step creative workflows
• Build intelligent capabilities for Firefly AI Assistant and Creative Cloud workflows
• Develop scalable services and APIs integrating AI and machine learning into Adobe products
• Drive the end-to-end ML lifecycle, including problem formulation, modeling, experimentation, evaluation, deployment, monitoring, and iteration
• Partner with engineering, product, design, and research teams to translate customer needs into ML solutions
• Improve performance, scalability, reliability, and quality of AI systems in high-traffic production environments
• Provide technical leadership and mentor engineers
• Identify opportunities to apply generative and agentic AI to challenges for creative professionals and enterprise customers

Staff Machine Learning Engineer

Product Manager

• Collaborate with cross-functional teams to analyze market trends and shape product vision and strategy
• Work with Engineering, Design, and Marketing to develop product strategies and features
• Conduct customer interviews, data analysis, and market studies
• Translate findings into product requirements, user stories, and roadmap recommendations
• Present insights and concepts to stakeholders and build alignment across teams
• Share narratives that inform vision, guide decisions, and inspire innovation
• Support initiatives that deliver measurable value for customers and the business

Product Manager, MBA Graduate

Artificial Intelligence

• Partner with EX process and service leads on the Transformation Office's top initiatives
• Turn priority opportunities into working AI solutions and assess which problems are worth solving with AI
• Design, build, and deploy full stack systems spanning frontend, backend, and AI integration
• Own projects from prototype to production and partner with technology teams on integrations
• Develop reusable patterns and tools for the Transformation Office
• Present findings, demos, and recommendations to collaborators and leadership
• Pilot Adobe's AI products on internal problems as Customer Zero

AI Forward Deployed Engineer

AI Engineer

• Serve as lead technical point of contact across multiple concurrent customer engagements
• Build enterprise architectures and roadmaps incorporating RAG, AI agents, and automated workflows
• Evaluate clients' existing architecture and AI/LLM preparedness and identify gaps to the desired state
• Align business strategy, IT roadmaps, and delivery teams building AI-powered features
• Define governance models covering data privacy, consent, access controls, and responsible-AI guardrails
• Recommend measurement frameworks for AI output quality, accuracy, cost, and latency
• Advise on AI security architecture, including prompt-injection defenses
• Document reference architectures for RAG, agent orchestration, and LLM integration patterns
• Engage marketers, analysts, developers, data scientists, and C-level executives through workshops and deliverables
• Provide enablement and mentoring on product features and AI optimization
• Translate LLM architecture concepts into technical writing and executive presentations
• Manage expectations, scope, and timelines across engagements
• Build trusted advisor relationships with enterprise clients

Program Manager – IT

Staff Security Data Engineer

Senior Designer

Software Development Engineer

Senior Videographer, Social Creative

University Graduate – Machine Learning Engineer

Software Engineer, University Graduate

Software Development Engineer

Marketing Strategy – Operations Director

Policy and Incident Specialist

Data Product Engineer

Staff Machine Learning Engineer

Product Manager, MBA Graduate

AI Forward Deployed Engineer

Enterprise AI Architect