Director of Production Support Engineering

Salesforce•Seattle, WA

1d•$197,300 - $344,700•Hybrid

About The Position

This is a unique leadership opportunity to manage the production excellence of a high-growth AI product while balancing a complex technical landscape: from our modern Salesforce-native deployment to legacy environments and highly specialized custom deployments for global tier-one customers. Join an agile team with deep startup roots. We operate as a high-velocity ‘startup-within-Salesforce,’ following our recent acquisition. We have successfully navigated the "0 to 1" journey and are now scaling Agentforce for Supply Chain from 1 to 100. This involves moving beyond a single-stack startup architecture into a sophisticated, multi-environment global operation that serves the world’s largest enterprises and government entities.

Requirements

10+ years of experience in Production Engineering, SRE, or Infrastructure roles, with at least 3-5 years in a formal people management capacity.
Deep Technical Roots: You must remain highly technical. You are comfortable reviewing architecture designs for Kubernetes, Terraform, and distributed databases (PostgreSQL), and you understand the operational nuances of AI/GPU workloads.
Experience at Scale: A proven track record of managing production environments through a "1 to 100" scaling phase, ideally in a multi-region or multi-cloud context.
Strategic Clarity: Demonstrated ability to articulate a complex technical vision and turn it into an actionable roadmap that stakeholders can rally behind.
Enterprise Savvy: Experience supporting "Big Iron" enterprise customers with custom deployment needs and high-compliance requirements.
High-Stakes Leadership: Proven ability to lead through major incidents and complex architectural migrations with a calm, decisive approach.
AI-Forward Mindset: Experience leveraging AI tools to optimize team workflows and a clear vision for how AI will transform the future of production support.
A demonstrated, genuine AI-first approach to engineering. Using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows
Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.

Nice To Haves

Experience with Government/Sovereign Clouds: Direct experience navigating FedRAMP, IL5/IL6, or similar high-security compliance frameworks.
Salesforce Infrastructure Knowledge: Familiarity with Hyperforce, Salesforce Data Cloud, or the internal mechanics of a "Private Cloud Edition."
Hybrid Infrastructure: Experience managing the bridge between public cloud (AWS/GCP/Azure) and specialized enterprise environments.
Advanced Degree: M.S. in Computer Science or a related technical field.

Responsibilities

Devise and champion a long-term infrastructure strategy that balances rapid AI product innovation with the rigorous demands of enterprise-grade reliability and global scale.
Manage and grow a world-class team of Production Support Engineers. You will be responsible for technical mentorship, career development, and maintaining a high-performance, low-ego culture.
Lead the transition to a multi-region and multi-substrate deployment model within the Salesforce commercial cloud, ensuring our "Super Agent" architecture is resilient across global geographies.
Oversee the maintenance and support of our legacy environments and bespoke customer deployments, ensuring a seamless experience for long-term partners as they transition toward our modern stack.
Act as the primary stakeholder for our Private Cloud (PCE) and Government Cloud initiatives, ensuring our infrastructure meets strict regulatory and data-residency requirements without sacrificing developer velocity.
Define and hold the team accountable to SLIs, SLOs, and error budgets. You will lead the "incident-to-insight" loop, ensuring production issues result in structural improvements to the product.
Collaborate with Product, Engineering, and Security leadership to align infrastructure investments with the broader business goals of the Agentforce ecosystem.
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance