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Director of Production Support Engineering

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Salesforce
Full Time position
Listed on 2026-05-05
Job specializations:
  • IT/Tech
    Systems Engineer, Cloud Computing, AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

What You’ll Do

As the Director of Production Support Engineering, you will be the strategic leader and people manager for our embedded reliability organization. You will lead a high-caliber team of Lead and Principal Engineers (LMTS/PMTS) who are integrated directly into the product lifecycle. Your responsibilities include defining the roadmap for scaling our commercial Salesforce offering into a multi-region, multi-substrate powerhouse, overseeing the stability of legacy and custom enterprise environments, and serving as the lead architect for our Private Cloud Edition (PCE) and Government Cloud initiatives.

Responsibilities
  • Strategic Roadmap & Vision:
    Devising and championing a long-term infrastructure strategy that balances rapid AI product innovation with enterprise-grade reliability and global scale.
  • People Leadership:
    Managing and growing a world-class team of Production Support Engineers, providing technical mentorship and career development while maintaining a high‑performance, low‑ego culture.
  • Multi-Substrate Scaling:
    Leading the transition to a multi-region and multi-substrate deployment model within the Salesforce commercial cloud, ensuring the Super Agent architecture is resilient across global geographies.
  • Legacy & Custom Operations:
    Overseeing the maintenance and support of legacy environments and bespoke customer deployments, ensuring seamless experiences as partners transition to the modern stack.
  • Compliance & Sovereignty Strategy:
    Acting as the primary stakeholder for PCE and Government Cloud initiatives, ensuring infrastructure meets regulatory and data‑residency requirements without sacrificing developer velocity.
  • Operational Excellence:
    Defining and holding the team accountable to SLIs, SLOs, and error budgets; leading the incident‑to‑insight loop to turn production issues into structural improvements.
  • Stakeholder Management:
    Collaborating with Product, Engineering, and Security leadership to align infrastructure investments with broader business goals of the Agentforce ecosystem.
  • Building High-Quality Software:
    Delivering production‑grade software using modern engineering practices, integrating AI into development workflows to optimize code quality and security.
  • Designing AI-Integrated Systems:
    Orchestrating complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
  • Maintaining System Context:
    Contributing to shared system context repositories that enable AI to operate reliably and accurately.
  • Code Evaluation:
    Critically evaluating code—human or AI-generated—for correctness, quality, security, and performance.
Required Qualifications
  • 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:
    Proficiency with Kubernetes, Terraform, and distributed databases such as Postgre

    SQL; understanding of AI/GPU workload operational nuances.
  • Experience at Scale:
    Proven track record managing production environments through a 1 to 100 scaling phase, ideally in a multi-region or multi-cloud context.
  • Strategic Clarity:
    Ability to articulate complex technical visions and translate them into actionable roadmaps.
  • Enterprise Savvy:
    Experience supporting large enterprise customers with custom deployment needs and high‑compliance requirements.
  • High‑Stakes Leadership:
    Demonstrated capability to lead through major incidents and complex architectural migrations with calm, decisive approach.
  • AI-Forward Mindset:
    Leveraging AI tools to optimize team workflows and envisioning AI’s future impact on production support.
  • AI‑First Engineering Approach:
    Using AI to move faster, building fluency across the stack, and contributing beyond core specialty.
  • Experience with AI tools (e.g., Claude Code, Git Hub Copilot, Codex, Cursor).
  • Advanced Prompt Engineering:
    Ability to write precise, structured prompts and cultivate system context to ensure AI outputs are reliable, secure, and production‑ready.
Preferred Qualifications
  • Experience with Government/Sovereign Clouds, e.g., navigating FedRAMP, IL5/IL6 compliance frameworks.
  • Salesforce Infrastructure Knowledge:
    Familiar it…
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