Staff Software Engineer, AI Systems

About Dolby Cloud Solutions

Dolby Cloud Solutions specializes in video streaming software that empowers enterprise and mid-market organizations to deliver superior audio and video experiences. Their flagship SaaS platform, Dolby OptiView, caters to customers in media, advertising, and real-time communication sectors with a mission to democratize immersive video experiences.

Role Overview

At the heart of embedding AI into its core processes, Dolby Cloud Solutions seeks a Staff Software Engineer to lead the technical architecture for shared AI infrastructure. This is a pivotal position responsible for defining standards, integration patterns, and serving as the technical authority for architectural decisions. The role involves close collaboration with business stakeholders to define needs and lead end-to-end solution builds, as well as partnering with Product Engineering teams on shared infrastructure and platform features.

Key Responsibilities

• Design and govern the technical architecture of the shared data and integration layers, setting standards and patterns for team adoption.
• Develop and enforce integration frameworks, credential management protocols, and scalable data access models across various teams and systems.
• Ensure infrastructure security, observability, and operational readiness beyond initial functionality.
• Architect and implement foundational data layers enabling reliable AI agent and application operations across business functions.
• Build and maintain integrations among key business systems including CRM, billing, support, and product usage platforms.
• Coordinate with Product Engineering on infrastructure, integration, and platform capability development, discerning when to build versus align.
• Manage MCP servers and API connectivity to internal systems with secure credential practices.
• Establish shared hosting solutions for agents, automations, and applications, migrating workflows off local devices into production environments.
• Create dependable scheduled automations and event-driven workflows requiring no manual intervention.
• Engage with business teams to clarify problems, refine requirements, define acceptance criteria, and lead delivery of tailored AI-driven applications and workflows.
• Iterate rapidly by deploying software, gathering feedback, and enhancing solutions continuously.
• Set organizational standards for AI system development, integration, and maintenance, providing reusable resources such as prompts, agents, skills, and workflows across teams.
• Empower colleagues across various departments to deploy AI solutions leveraging shared infrastructure.

Candidate Profile

• Minimum 5 years of experience designing and delivering production software including applications, APIs, backend services, platform infrastructure, or data integrations, with proven use of AI-assisted development tools like Devin, Claude, Codex, or Cursor to accelerate engineering productivity.
• Proven architectural leadership with the ability to establish technical standards and shape engineering practices within an organization.
• Strong programming skills in Python or TypeScript/Node.js, with aptitude to learn additional technologies as needed.
• Experience in developing tool integrations for AI systems, ideally familiar with Model Context Protocol (MCP) or similar frameworks.
• Demonstrated skill integrating with SaaS APIs using REST, webhooks, OAuth, handling real-world edge cases.
• Hands-on expertise using large language model (LLM) APIs and agentic frameworks to build production-ready AI agents and workflows beyond prototyping.
• Ability to collaborate effectively with business stakeholders, facilitating requirements gathering, critical questioning, constructive feedback, and translating business needs into functional software.
• Experienced working with product and platform engineering teams, articulating requirements, aligning on approaches, and facilitating cross-team execution.
• Strong emphasis on security: knowledgeable about data classification, access controls, credential management, compliance, and risk management, applying these principles in system design and operation.

Preferred Qualifications

• Experience designing federated data architectures, shared integration frameworks, or complex multi-system data pipelines.
• Familiar with prevalent SaaS systems for revenue, support, and customer success operations.
• Background experience in Customer Success, Revenue Operations, or B2B SaaS businesses, providing domain insight into the systems being developed.
• Proven ability to incorporate data classification, compliance protocols, security, and risk assessments within AI-powered systems and automations.