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Key statistics

The identity block — every fact is canon, none is generated.

5 of 8

Track

Management

Family rungs priced

—

15-0000

—

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Senior leader who directs the organization's DevOps and site reliability engineering function, setting strategy and overseeing multiple teams responsible for platform reliability and delivery velocity. At the Senior Director (M5) level, the role owns multiple functions or a large department, org-level trade-offs and investment, and drives multi-function results. Leads directors and managers.

What this level does

Directs the DevOps/SRE organization through subordinate managers, with decisions impacting division-wide or company operations and the reliability of all customer-facing services
Solves complex org-wide reliability problems and defines the methods, SLO governance, and error-budget policy that engineering divisions operate under
Influences executives and major customers on reliability commitments, availability targets, and the balance of feature velocity against operational risk
Sets the multi-year automation, observability, and infrastructure-as-code roadmap that determines how safely and frequently the whole engineering org can ship
Owns the division's reliability budget and organizational design, leading through managers to build durable operational-excellence capability

Knowledge applied: Defines methods and governance for complex org-wide reliability, impacting division or company operations.
Complexity & problem solving: Solves complex organization-wide reliability issues and defines the operating methods and SLO governance.
Collaboration & interaction: Influences executives and major customers on reliability commitments and risk trade-offs.
Typical experience: 10–12+ years, second-level management and strategy work; leads through department managers.

Skills at this level

SLO/SLI and Error Budget Governance: — Defines and meets SLOs for core platform services and governs error-budget policy, arbitrating when customer-visible burn requires prioritizing reliability work over feature delivery.
Incident Management and On-Call Leadership: — Establishes triage approach for alerts and incidents, owns on-call rotations, and leads major-incident response and post-incident corrective-action programs that reduce recurring failures.
Infrastructure as Code: — Directs Terraform/IaC automation of shared infrastructure and production environments — the most consequential change surface — setting standards for how provisioning changes are reviewed and shipped safely.
Monitoring and Observability: — Owns the observability strategy for tracking system health and signals, improving dashboard, alert, and SLO-reporting quality so engineering teams get trustworthy signal and can ship safely.
Deployment Automation and Delivery Enablement: — Builds and oversees delivery pipelines and operational controls that let engineering ship frequently and reliably, increasing deployment consistency and reducing manual toil through automation.
Reliability Engineering Program Ownership: — Owns reliability within and across system boundaries, scaling practice from team-scoped to platform- and org-scoped, and directing capacity, resilience, and time-to-recovery improvements.
Automation Scripting Direction (Python/Go/Bash): — Guides use of Python or Go for automation and tooling and bash for operational scripts, prioritizing which manual work to eliminate to increase operational capacity.
Team Leadership and Budget Management: — Hires, develops, and manages SRE professionals and subordinate managers, owning operational budgets and capacity/tooling investment planning for the reliability function.
Reliability Strategy and Policy Setting: — Sets strategic reliability policy and long-term automation/observability roadmaps aligned to business objectives, determining how safely and frequently the engineering organization operates.
Executive and Customer Reliability Stakeholder Management: — Influences executives and major customers on availability commitments and reliability trade-offs, negotiating platform-investment and error-budget decisions at the org level.

Model-authored from 20 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

No priced rungs for this family's ladder yet.

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

SOC 15-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

-10.1%Network and Computer Systems Administrators · United States

354,450 → 318,570 jobs

14,300 openings / year, split into:

replacement / exits 15,692

Growth — new jobs (-10%)Exits — backfill (100%)

This occupation is projected to contract — every opening is replacing someone leaving, not net new demand.

Projected growth 2024–34 contracting: -4.2%
Growth share of hiring: -10%
Exit / retention pressure high: 100%
Openings / year: 14,300

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where this role sits — growth vs. pay

level M5 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$314k

San Francisco-Oakland-Fremont, CA$281k

Washington-Arlington-Alexandria, DC-VA-MD-WV$260k

Boulder, CO$257k

Seattle-Tacoma-Bellevue, WA$257k

Boston-Cambridge-Newton, MA-NH$246k

Lexington Park, MD$240k

Trenton-Princeton, NJ$238k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $188k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates M5 (M5 — Senior Director) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple functions or a large department
Autonomy: Owns multi-year strategy for the area
Complexity: Org-level trade-offs and investment
Impact: Multi-function results
Decision rights: Owns investment and org design across functions
Leadership: Leads directors and managers

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

The next rung from M5 is M6.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
Director of Cost Accounting	jfo_jfm_accounting-cost-accounting::M5	—	confident0.00
Director, General Accounting	jfo_jfm_accounting-general-accounting-management::M5	—	confident0.00
Director, General Accounting	jfo_jfm_accounting-general-accounting::M5	—	confident0.00
Director of Administrative Services	jfo_jfm_administrative-corporate-services-administrative-services-ma::M5	—	confident0.00

Capability cluster

O*NET 15-1244

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

M5

jfo_jfm_infrastructure-devops-sre-devops-site-reliability-engineerin::M5

Director of DevOps & Site Reliability Engineering

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: M
Universal level: 5 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

jfo_jfm_accounting-cost-accounting::M5 · M5confident0.00

jfo_jfm_accounting-general-accounting-management::M5 · M5confident0.00

jfo_jfm_accounting-general-accounting::M5 · M5confident0.00

jfo_jfm_administrative-corporate-services-administrative-services-ma::M5 · M5confident0.00

jfo_jfm_administrative-corporate-services-administrative-support::M5 · M5confident0.00

jfo_jfm_administrative-corporate-services-service-delivery::M5 · M5confident0.00

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 15-1244	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)