Senior Software Engineer, Meta Factory Skills

About the role

The Opportunity Adobe Unified Platform is building the system that changes how software gets made at Adobe. Meta Factory is the core of that platform: the Agentic Builders Experience that defines how agents understand their goals, decompose work, use tools, evaluate their own outcomes, and improve over time.

Responsibilities

• Shape the technical direction of the Agent Harness across agent execution, tool use, context, state, and lifecycle management.
• Define clear interfaces and standards for how agents, tools, and Meta Factory interact with the harness.
• Evaluate emerging agent runtime and tool-use patterns, and help teams adopt the right approaches for Adobe’s needs.
• Build reusable architecture patterns for agentic systems that are secure, scalable, and maintainable.
• Lead cross-team technical work and help resolve complex design challenges across Meta Factory and partner teams.
• Share expertise through design docs, technical reviews, internal forums, and mentoring engineers working on agentic systems.

Requirements

• 12+ years of software engineering experience, with a track record of delivering high-impact systems used by multiple teams or products.
• Strong expertise in distributed systems, runtime design, and platform architecture.
• Experience building agentic systems, LLM infrastructure, developer platforms, or other AI-enabled systems.
• Proven ability to design scalable systems that balance near-term delivery with long-term maintainability.
• Experience leading complex technical work across teams, including design reviews, implementation planning, and technical decision-making.
• Ability to influence engineering teams and align stakeholders around clear, practical architectural choices.
• Strong written and verbal communication skills, including experience writing design documents and sharing technical knowledge across teams.
• Experience mentoring engineers and helping teams adopt new technologies and engineering patterns.

Qualifications

• Experience with agent runtimes, model context protocols, multi-agent coordination, tool calling patterns, sandboxed execution, and feedback-driven improvement systems.
• Deep expertise in building systems that support complex workflows and automated processes.
• Knowledge of modern software development practices, including agile methodologies and continuous integration/continuous deployment (CI/CD).
• Experience with cloud-based services and infrastructure, such as AWS, Azure, or Google Cloud.

Skills

• Proficiency in programming languages commonly used in AI and machine learning projects, such as Python, Java, or C++.
• Experience with distributed systems and microservices architectures.
• Understanding of computer science fundamentals, including algorithms, data structures, and complexity theory.
• Experience with testing frameworks and tools, such as JUnit, PyTest, or Jest.
• Knowledge of DevOps practices and tools, including containerization (Docker, Kubernetes), orchestration (Kubernetes), and monitoring (Prometheus, Grafana).

Benefits

• Comprehensive health and wellness benefits, including medical, dental, vision, and mental health coverage.
• Flexible spending accounts for healthcare and dependent care expenses.
• Retirement savings plans, including 401(k) and IRA contributions.
• Generous paid time off, including vacation, sick leave, and parental leave.
• Employee resource groups and diversity, equity, and inclusion initiatives.
• Professional development opportunities, including training and certification programs.
• Work-life balance, including remote work options and flexible schedules.

Pay

• Expected Pay Range: $173,500 -- $331,050 annually.
• Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience.

Schedule

• Full-time position.