Own the technical program management operating system for a growing engineering organization. Establish planning, intake, prioritization, dependency, risk, incident, escalation, and delivery measurement mechanisms. Lead strategic cross-functional programs from definition through launch, improve operational workflows, communicate delivery risk to executives, and grow the program management function.
About BackOps
BackOps AI transforms supply-chain operations with agentic AI that automates complex workflows, freeing teams to focus on what matters most. Headquartered in the San Francisco Bay Area, we foster a culture of innovation, ownership, and measurable impact.
The Role
Engineering is at the size where the hardest problems stop being technical and start being cross-cutting. Work arrives from everywhere. Dependencies between teams get discovered late. Decisions that touch three teams wait on one person's calendar.
You would be our first Technical Program Manager, and you would own that layer. Not by adding process, but by building the smallest set of mechanisms that make the org self-coordinating, and then getting out of the way.
This role reports to the VP of Engineering with direct exposure to the CTO and the Head of Product. You will not be assembling status reports for a hierarchy. You will be deciding which programs exist and making them land.
Your Impact
- Own the operating system this organization runs on: the planning cadence, how work arrives, and how it gets prioritized. Programs are the output. The system is the job.
- Set the program agenda with the VP of Engineering. Decide which programs exist and which do not.
- Own our top strategic programs end to end, from framing the problem through to the thing being live and working.
- Build the dependency and risk picture across engineering, product, and customer delivery, and surface problems early enough that they are still cheap to fix.
- Fix how work arrives. Reducing unplanned work is one of the highest-leverage things anyone can do here.
- Own the operational programs that cross every team: incident and escalation design, cloud cost, and how we adopt AI tooling internally.
- Define the metrics that show whether a program is working, and give leadership a trustworthy read on delivery risk without anyone having to chase it.
- Grow other program managers as the function scales.
What We're Looking For
- 10+ years in technical program management, engineering, or a blend, including time at a startup where the process did not exist yet and you built it.
- You have owned an operating system, not just programs. Planning, intake, and prioritization as a system that keeps working after you stop pushing on it.
- Technical credibility with senior engineers and architects. You can hold architecture and delivery risk in the same conversation, read a design doc, ask the question that changes the design, and push back on an estimate with reasons. You do not need to write production code. You do need engineers to want you in the room.
- A track record of landing an organization's most important programs across teams that do not report to you.
- Experience growing other program managers, and shaping how an engineering organization works rather than only working inside it.
- Clear, compressed written communication. You can put a complicated delivery risk in front of an executive in a paragraph and have them make the right call.
- Comfort with genuine ambiguity. Several of the programs above do not exist yet and are yours to define.
Nice to Have
- AI/ML or agentic systems experience, especially the reliability and evaluation problems that come with non-deterministic software.
- You have built a planning or intake system from scratch and seen it survive a year.
- Enterprise or regulated-customer delivery experience.
- Incident and escalation program design.
What Success Looks Like
- Every cross-team initiative has an owner, a definition of done, and a status you can trust.
- Intake has a front door, and unplanned work is measured weekly rather than estimated once a year.
- The org plans and re-plans without it being an event.
- Escalation paths are designed, written down, and used in a real incident.
- Systemic problems get fixed once rather than escalated repeatedly.
- Leadership makes decisions on current information without anyone assembling it by hand.
Why BackOps
- A function to define rather than inherit, with the mandate and the executive backing to do it.
- Real scope: you will shape how a fast-growing engineering organization operates.
- Small team with real autonomy and direct access to founders and customers.
- Backed by exceptional investors and advisors.
Rewards
- Competitive salary and meaningful equity.
- Comprehensive health, dental, and vision coverage.
- 401(k) plan, disability insurance, and life insurance.
- Flexible time off.
- Daily meals in the office, and regular team events and offsites.
BackOps AI San Francisco, California, USA Office
San Francisco, CA, United States
BackOps AI San Ramon, California, USA Office
San Ramon, United States
Similar Jobs
Cloud • Information Technology • Machine Learning
Lead large-scale technical programs that improve engineering excellence across developer teams. Drive platform adoption, engineering and security standards, safer release practices, migration planning, exception management, and reduced deployment incidents. Partner with platform, infrastructure, security, reliability, observability, product, and engineering teams to improve developer velocity, release reliability, and operational efficiency. Provide program visibility, manage dependencies and risks, and align execution across teams without direct authority.
Top Skills:
Artifact ManagementBuild SystemsCi/CdConfluenceDependency ManagementDeveloper InfrastructureDistributed SystemsJIRAObservabilitySecrets ManagementSource ControlTest Systems
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Leads complex, cross-functional technical programs for the Superintelligence Lab. Responsibilities include roadmap execution, milestone and dependency management, risk mitigation, issue resolution, stakeholder alignment, leadership reporting, and implementing program-management best practices. The role requires collaboration with engineering, data science, and leadership teams while using AI technologies and Jira to improve workflows, decision-making, and business outcomes.
Top Skills:
AgileArtificial IntelligenceData ScienceJIRAKanbanMachine LearningScaled AgileScrum
Big Data • Cloud • Software • Database
Own MongoDB’s IT audit and governance program across applications, infrastructure, cloud, and business systems. Lead SOX ITGC and ITAC compliance, control design, evidence, readiness testing, remediation, audit coordination, and framework harmonization. Partner with IT, Finance, Legal, Internal Audit, and external auditors while driving accountability across teams. Establish governance standards, automate controls, reduce audit burden, and report risks and findings to senior leadership and the Audit Committee.
Top Skills:
ArcherAuditboardAWSAzureCi/CdCmdbDevOpsGCPIamInfrastructure-As-CodeNetSuiteOraclePower BIPythonSAPServicenow GrcSQLTableauWorkiva
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
