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Etched · San Jose, CA · posted 6 days ago
By AtiveSite · Published 07/11/2026 · Updated 10/11/2026 · Every figure is linked to its source below.
| Employer | Etched |
|---|---|
| Location | San Jose, California |
| Field | Technology › Cloud, IT and infrastructure |
| Level | not stated |
| Source category | Software, Software |
| Posted | 2026-11-04 (6 days ago) |
| Work arrangement | On-site at the location listed |
| Pay | Not published in the source listing |
About Etched
Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.
Job Summary
You'll be one of Etched's first Site Reliability Engineers, building the command-and-control layer for our fleet of frontier inference systems: the alerting, automated recovery and fleet data that keep clusters serving, and the routing that gets each problem to the right expert. Our Supercomputing and Infrastructure teams build the fleet management, rollout and telemetry backbone; but you'll decide which signals define a healthy system, set how we alert and respond, and build agentic hardware health workflows on top of it.
Your job is to design and run a scalable system. Fleet SREs own detection, first response and handoff; domain SREs embedded in each team own the deep product fixes. Over time, most problems should be caught by an alert that measures what users experience, which is then triaged by agents, and sent to an engineer as needed, with the logs, dashboards and recent changes already attached.
Key Responsibilities
Define what a healthy inference system looks like. In collaboration with software teams building out management and telemetry systems, identify the signals that most clearly show an unhealthy site, rack, node or chip, keep refining them as the fleet changes, and decide which actions (drain, cordon, restart, reroute, roll back) run on their own and which page a person.
Set a common alerting standard. Define SLOs with each team (latency such as time to first token, error rate, availability), alert on user-facing symptoms, and verify that the metrics behind each alert measure what the alert assumes.
Cut alert noise. Suppress expected alerts during deploys and maintenance automatically, correlate related alerts into one incident, and retire pages nobody acts on.
Automate recovery. Turn runbooks into agentic hardware health recovery: service restarts, node drain and traffic shift, spare swaps. Build it with guardrails (scoped permissions, rate limits, blast-radius checks, an audit trail)..
Route every event to the right engineer. Classify events by domain, page the right domain SRE with context attached, and dispatch on-site technicians for physical work such as tray swaps, reseats and leak response.
Shape the fleet data. Work with Supercomputing and Infrastructure, who build the telemetry pipeline, so it captures the key signals. Set the tracing standard (OpenTelemetry) so every service can be followed end to end, and report uptime and reliability trends that drive engineering and capacity decisions.
Run operationally excellent incident management. Own severity levels, incident channels, communications, postmortems and corrective-action tracking. Design on-call rotations, handoffs and onboarding so on-call is sustainable.
Raise the reliability bar for services. Review service designs with their owners for failure modes and graceful degradation before they ship, and partner with Supercomputing on canaries, rolling node-by-node deploys and graceful drain, so updates stop causing downtime.
Share on-call in a follow-the-sun rotation with SREs in other time zones.
Hands-on debug
Be the first line of defense. Acknowledge, size the user impact, open the incident, and decide fast between restart, drain, rollback and escalation.
Find where requests are stuck. Trace a latency or throughput regression through the serving stack (queueing, prefill, decode, handoffs, cache) to the stage that's backing up.
Triage hardware on live racks. Work through errors: chips dropping off PCIe, firmware panic resets, chip-to-chip link errors, HBM ECC errors and power faults; run recovery tools and decide when a node comes out.
Correlate across layers. Follow a request end to end with distributed traces (OpenTelemetry), then line up deploys, firmware events, host and BMC logs, network data and facilities telemetry to tell a software bug from a hardware fault from a coolant or power event.
Check the alert, not just the system. When a page and a dashboard disagree, work out which one is wrong: a capped metric, a stale exporter or a failed scrape.
Direct hands on site. Walk on-site technicians through reseats, PSU and tray swaps, and leak response with exact steps.
Hand off cleanly. Leave a timeline, evidence and current hypothesis so the domain SRE or next shift picks up without starting over.
Close the loop. Turn every manual fix into a runbook, then into tasks that can be executed by agents, so the same page doesn't wake anyone twice.
You may be a good fit if you have (Must-have qualifications)
2+ years in site reliability, production engineering or infrastructure for large-scale production systems (8+ years for the San Jose lead seat).
You've defined alerting standards that several teams adopted, using Prometheus, Grafana or similar, and you know SLOs, error budgets and alert design well enough to teach them.
Real on-call experience for services with external users, including leading incidents and writing blameless postmortems.
A track record of debugging production incidents in systems you didn't write, under time pressure, from logs, metrics, traces and core dumps.
Experience with application and scripting languages like python, golang, rust, etc.
Hands-on with Linux, containers, Kubernetes and infrastructure as code (Terraform, Ansible or similar).
Fluency with Linux debugging tools (perf, strace, gdb, dmesg, journalctl, lspci, tcpdump) for when the dashboards don't have the answer.
Comfort with hardware in the loop: devices dropping off PCIe, ECC errors, power and thermal events, and failures that cross software and physical layers.
Sound judgment about when automation should act on its own and when it should page a person.
Clear writing, and the ability to get five or more teams to agree on shared standards.
Strong candidates may also have experience with (Nice-to-have qualifications)
Operated GPU, accelerator or HPC fleets.
LLM inference serving: prefill and decode, KV cache, batching, and latency metrics such as time to first token.
Network debugging from switch to edge: tracing problems across switches, load balancers and Cloudflare, and using edge controls like rate limits to shed or shift traffic during an incident.
Out-of-band management (BMC, Redfish, IPMI) and fleet-wide firmware rollouts.
Data center telemetry: power distribution, liquid cooling and CDUs, DCIM.
PagerDuty or similar incident tooling, including event correlation and automated remediation.
Working with colocation providers and remote-hands technicians.
Founding or scaling an SRE function at a startup.
Benefits
Medical, dental, and vision packages with generous premium coverage
$500 per month credit for waiving medical benefits
Housing subsidy of $2,500 per month for those living within walking distance of the office
Relocation support for those moving to San Jose (Santana Row)
Various wellness benefits covering fitness, mental health, and more
Daily lunch and dinner in our office
Unlimited compute budget subject to ROI justification
How we’re different
Etched believes in the Bitter Lesson. We are the first inference-focused frontier AI system, betting early on transformer and transformer-like architectures and on increasing model sizes. Our addressable market is the entirety of inference, unlike many of our competitors.
We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Field: Technology Sub-niche: Cloud, IT and infrastructure All jobs at Etched Jobs in California Jobs in San Jose, CA San Jose city guide California state guide Santa Clara County economy
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This is a — role in the Technology field (Cloud, IT and infrastructure) at Etched.
We could not match this job title to one occupation in the official wage statistics, so no pay estimate is shown. Pay is not in the source listing; ask the employer for the range and compare in the 240 job niches.
Estimate for a wage earner: 2026 federal brackets and standard deduction (IRS), Social Security 6.2% up to $184,500, Medicare 1.45% (+0.9% above $200,000 single / $250,000 married), and a state rate you set; set your own state tax rate. It ignores credits, pre-tax deductions, local taxes and benefits. Sources: IRS: tax year 2026 inflation adjustments · SSA wage base per Federal Register notice 2025-19763.
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The job is in San Jose, CA. Below is what the official statistics say about living and working there.
How San Jose compares. Among the 145 largest places in California, San Jose is #3 by population, #30 for household income (#1 = highest), #110 for rent (#1 = cheapest), #48 for college degrees (#1 = most). Its county, Santa Clara County, is #1 of 58 counties for average pay ($197,043).
San Jose has 990,138 residents (ACS 2020–2024), about 2.5% of the population of California. It covers 178 square miles of land, which works out to roughly 5,564 people per square mile. The median age is 38.2, about the same as the state median (38.2 against 37.9).
The median gross rent is $2,669 a month (rent plus utilities), 31% above the state median ($2,669 against $2,036). Over a year that is 21.9% of the median household income. US housing guidance treats housing as affordable when it takes 30% of income or less, so the typical household is under that line. The median home value is $1,233,200, which is 8.4 times the median household income ($146,427); a ratio above 5 usually means buying is out of reach without savings or a second income. 55.8% of households own their home, about the same as the state average (55.8% against 55.9%).
The San Jose-Sunnyvale-Santa Clara, CA metropolitan area has 1,134,970 jobs in the BLS wage survey, and the median pay across all occupations is $84,050 a year, 65% above the national median ($84,050 against $50,980). The biggest occupation groups are computer and mathematical (149,970 jobs, median $186,320); management (115,110 jobs, median $210,750); business and financial operations (94,210 jobs, median $125,240). The area is most specialised in computer and mathematical (3.9 times) and architecture and engineering (2.5 times), where the share of workers is well above the national share. The best-paying groups with at least 5,000 jobs are management ($210,750) and legal ($195,190). In 2026M09 the unemployment rate of Santa Clara County was 4.2%. 67.6% of residents aged 16 and over are in the labour force. The city lies in Santa Clara County; its jobs, pay by industry and GDP are on the county page.
Among workers, 62.9% drive alone, 2.4% use public transit, 1.8% walk, 20.3% work from home. 15.3% of workers commute 45 minutes or more, 21% below the state average (15.3% against 19.4%).
47.3% of adults aged 25 and over hold a bachelor's degree or higher, 28% above the state share (47.3% against 37.1%). 42.0% of residents were born outside the United States, 56% above the state share (42.0% against 27.0%). The poverty rate is 8.1%, 32% below the state rate (8.1% against 12.0%).
The warmest month is Aug, averaging 68°F (19.8°C), and the coolest is Jan at 47°F (8.3°C). About 510 mm (20 inches) of precipitation falls in a year; Dec is the wettest month (114 mm) and Jul the driest (0 mm). These values come from NASA satellite-based climatology on a grid of about 50 km, so they describe the wider area, not a weather station in the city.
Closest cities in this guide: Campbell (8 miles, similar rent); Los Gatos (9 miles, rent 22% higher); Santa Clara (10 miles, rent 13% higher); Milpitas (10 miles, rent 17% higher). Rent differences are against San Jose; use the Compare tab to put any two cities side by side.
Full guide to San Jose →California guideAll jobs in San Jose
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Places within 50 miles (straight line) of San Jose, CA that have a guide, with what living there costs. No pay estimate is shown because the title did not match one occupation.
| Place ⇅ | Distance from the job city ⇅ | Median rent ⇅ | Median home value ⇅ | Median household income ⇅ | Commute 45+ min ⇅ | Rent as % of occupation pay ⇅ | Open jobs there ⇅ |
|---|---|---|---|---|---|---|---|
| San Jose, CA | 0 mi | $2,669 | $1,233,200 | $146,427 | 15.3% | n/a | Jobs |
| Campbell, CA | 8 mi | $2,737 | $1,617,000 | $145,268 | 10.4% | n/a | Jobs |
| Los Gatos, CA | 9 mi | $3,247 | $2,000,001 | $217,554 | 17.6% | n/a | — |
| Santa Clara, CA | 10 mi | $3,016 | $1,582,600 | $178,958 | 8.9% | n/a | Jobs |
| Milpitas, CA | 10 mi | $3,120 | $1,251,700 | $178,798 | 15.2% | n/a | Jobs |
| Saratoga, CA | 12 mi | $3,501 | $2,000,001 | $250,001 | 8.3% | n/a | — |
| Cupertino, CA | 13 mi | $3,501 | $2,000,001 | $234,707 | 9.1% | n/a | Jobs |
| Sunnyvale, CA | 13 mi | $3,039 | $1,801,800 | $186,170 | 9.0% | n/a | Jobs |
| Morgan Hill, CA | 15 mi | $2,474 | $1,210,200 | $163,920 | 32.9% | n/a | — |
| Fremont, CA | 15 mi | $2,933 | $1,403,800 | $181,506 | 23.6% | n/a | Jobs |
| Mountain View, CA | 16 mi | $3,062 | $1,927,000 | $189,917 | 9.3% | n/a | Jobs |
| Los Altos, CA | 16 mi | $3,501 | $2,000,001 | $250,001 | 8.3% | n/a | — |
| Los Altos Hills, CA | 18 mi | $3,501 | $2,000,001 | $250,001 | 18.0% | n/a | — |
| Newark, CA | 19 mi | $2,776 | $1,142,800 | $169,064 | 22.2% | n/a | Jobs |
| Palo Alto, CA | 19 mi | $3,484 | $2,000,001 | $231,101 | 8.2% | n/a | Jobs |
| East Palo Alto, CA | 21 mi | $2,244 | $1,102,600 | $113,493 | 9.7% | n/a | — |
| Menlo Park, CA | 22 mi | $3,239 | $2,000,001 | $210,025 | 11.5% | n/a | Jobs |
| Gilroy, CA | 24 mi | $2,301 | $1,027,400 | $133,107 | 32.4% | n/a | — |
| Atherton, CA | 24 mi | $3,501 | $2,000,001 | $250,001 | 7.0% | n/a | — |
| Union City, CA | 24 mi | $2,713 | $1,104,900 | $133,715 | 24.0% | n/a | — |
We could not match this title to one occupation, so here are the other sub-niches in Technology, where your skills may carry over:
Cybersecurity (760) Data, analytics and AI (3724) Software engineering (4655) Product management (935)
How far San Jose, CA is from the 20 largest US cities, in straight-line miles (not driving distance). Click a column to sort.
| From ⇅ | Straight-line distance (miles) ⇅ | Population of that city ⇅ |
|---|---|---|
| San Jose, CA | 0 mi | 990,138 |
| San Francisco, CA | 73 mi | 830,235 |
| Los Angeles, CA | 296 mi | 3,857,263 |
| San Diego, CA | 407 mi | 1,389,526 |
| Phoenix, AZ | 604 mi | 1,642,323 |
| Seattle, WA | 714 mi | 754,195 |
| Denver, CO | 930 mi | 718,877 |
| Oklahoma City, OK | 1,354 mi | 697,125 |
| Fort Worth, TX | 1,414 mi | 963,194 |
| San Antonio, TX | 1,444 mi | 1,479,835 |
| Dallas, TX | 1,446 mi | 1,307,930 |
| Austin, TX | 1,459 mi | 979,539 |
| Houston, TX | 1,602 mi | 2,328,253 |
| Chicago, IL | 1,832 mi | 2,711,226 |
| Indianapolis, IN | 1,923 mi | 885,860 |
| Columbus, OH | 2,087 mi | 914,802 |
| Charlotte, NC | 2,270 mi | 903,844 |
| Jacksonville, FL | 2,337 mi | 977,670 |
| Philadelphia, PA | 2,497 mi | 1,579,706 |
| New York, NY | 2,550 mi | 8,483,844 |
| City ⇅ | Straight-line distance ⇅ | Open jobs ⇅ |
|---|---|---|
| Campbell, CA | 8 mi | 7 |
| Milpitas, CA | 10 mi | 15 |
| Sunnyvale, CA | 13 mi | 185 |
| Fremont, CA | 15 mi | 8 |
| Palo Alto, CA | 19 mi | 330 |
| Capitola, CA | 23 mi | 1 |
| Pleasanton, CA | 26 mi | 7 |
| Redwood City, CA | 27 mi | 47 |
| Belmont, CA | 30 mi | 2 |
| Alameda, CA | 39 mi | 37 |
| San Francisco, CA | 73 mi | 3,425 |
| Sacramento, CA | 90 mi | 56 |
Etched is the employer in this listing. See all its open jobs here →
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A private-sector role in technology (cloud, it and infrastructure) listed 6 days ago. The full description is on this page and on the employer's page.
San Jose, CA.
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The listing does not publish pay, and we could not match the title to one official occupation.
Median rent in San Jose is $2,669 a month and median household income $146,427 (ACS 2020–2024).
It was posted on 2026-11-04 (6 days ago). Jobs older than 90 days are not shown.
Yes: browse cloud, it and infrastructure jobs in California.
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