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Associate Ai Infrastructure Engineer Jobs in California

F2 AI

Infrastructure Engineer

San Francisco, CA · On-site

$120 - $160/hr

Design and build scalable infrastructure to support our AI-powered knowledge engine processing ... engineering * Strong background in cloud platforms (AWS, GCP, or Azure) with expertise in ...

Tencent

Sr. Cloud AI Infrastructure Engineer

Palo Alto, CA · On-site

$151K - $283K/yr

... infrastructure. Who We Look For 1.Education: Master's or Ph.D. degree in Computer Engineering ... Expertise in GPGPU architectures or other mainstream AI accelerator architectures . 3.Programming ...

NIO

Sr/Staff AI Infrastructure Engineer

San Jose, CA · On-site

$163K - $212K/yr

Partner with engineering teams to understand real-world constraints and to support the high-quality ... AI extension/application/project * Experience with cloud infrastructure and training (Azure, AWS ...

Accenture

AI Infrastructure Operations Engineer

San Diego, CA · Hybrid

$114K - $149K/yr

The Global AI Infrastructure team enables resilient, high-performance compute environments for ... Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must ...

NIO

Sr/Staff AI Infrastructure Engineer

San Jose, CA · On-site

$163K - $212K/yr

Partner with engineering teams to understand real-world constraints and to support the high-quality ... AI extension/application/project * Experience with cloud infrastructure and training (Azure, AWS ...

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All JobsAssociate Ai Infrastructure Engineer JobsAssociate Ai Infrastructure Engineer Jobs in California

Associate Ai Infrastructure Engineer information

What is the difference between Associate Ai Infrastructure Engineer vs Data Engineer?

AspectAssociate Ai Infrastructure EngineerData Engineer
Required CredentialsBachelor's in CS, Engineering, or related field; familiarity with cloud platformsBachelor's in CS, Data Science, or related; strong programming skills
Work EnvironmentAI/ML teams, cloud environments, infrastructure setupData pipelines, database management, data processing systems
Employer & Industry UsageTech companies, AI startups, cloud service providersTech firms, finance, healthcare, data-driven industries

Associate Ai Infrastructure Engineers focus on building and maintaining AI infrastructure, while Data Engineers develop and manage data pipelines and databases. Both roles require technical skills and often collaborate, but their core responsibilities differ in infrastructure versus data processing.

How much do associate AI infrastructure engineers make?

Associate AI infrastructure engineers typically earn between $70,000 and $100,000 annually, depending on experience, location, and company size. Entry-level roles may start lower, while those with specialized skills in cloud platforms, machine learning tools, or certifications can earn higher salaries.

What are the most commonly searched types of Ai Infrastructure Engineer jobs in California?

The most popular types of Ai Infrastructure Engineer jobs in California are:

What are popular job titles related to Associate Ai Infrastructure Engineer jobs in California?

For Associate Ai Infrastructure Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Associate Ai Infrastructure Engineer jobs in California look for?

The top searched job categories for Associate Ai Infrastructure Engineer jobs in California are:

What cities in California are hiring for Associate Ai Infrastructure Engineer jobs?

Cities in California with the most Associate Ai Infrastructure Engineer job openings:

Associate Ai Infrastructure Engineer jobs near you
Infographic showing various Associate Ai Infrastructure Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Senior/Staff AI Infrastructure Engineer

Socket.dev

San Francisco, CA • On-site

$120 - $190/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago

Job description

About Echelon

Echelon is building the AI platform for Business Operations. Our goal is to automate the knowledge work of BizOps so one exceptional operator can deliver the leverage of an entire team, as Ramp and Rippling have done for Finance and HR.
Our platform combines passive process mining with a living ontology that maps how work happens across people, systems, documents, decisions, and outcomes. It connects structured and unstructured data trapped in fragmented, duplicative, and legacy enterprise systems, then turns that context into automated workflows and AI agents.
We are an early-stage company tackling a difficult technical problem at high speed. Engineers work directly with founders and customers, make decisions with incomplete information, ship production systems, and own the results. The pace, rate of change, and standards are high.

The mandate
Build the secure execution substrate for Echelon's agents. You will scale ep * * ​
What you’ll own
Design and operate sandbox lifecycle systems for agent code execution, browser work, document processing, and tool use.
Improve sandbox startup time, density, scheduling, warm pools, caching, and resource utilization.
Build fast, reliable filesystem primitives for ephemerate and persistent agent state, large artifacts, and concurrent workloads.
Enforce tenant isolation, network policy, secrets boundaries, quotas, and least-privilege access.
Make long-running agent jobs durable through checkpointing, retries, idempotency, cancellation, and recovery.
Scale orchestration and control-plane services through rapid workload growth and unpredictable bursts.
Build observability for resource pressure, execution failures, queue health, noisy neighbors, cost, and end-to-end latency.
Run load tests, capacity plans, failure drills, and incident reviews; fix root causes rather than adding fragile workarounds.

What you bring
5+ years building production infrastructure, distributed systems, developer platforms, or execution runtimes.
Hands-on ownership of containerized or virtualized workloads in a multi-tenant production environment.
Strong Linux systems knowledge across processes, filesystems, networking, resource isolation, and performance debugging.
Experience with Kubernetes or a comparable scheduler, infrastructure as code, and cloud primitives on AWS or Azure.
Strong programming ability in Go, Rust, TypeScript, Python, or another systems-oriented language.
Experience designing for retries, idempotency, backpressure, load shedding, observability, and safe rollouts.
Security instincts appropriate for executing untrusted or model-generated work.

Useful experience
Firecracker, gVisor, Kata Containers, namespaces/cgroups, seccomp, or eBPF.
Sandbox products such as E2B, Modal, Fly Machines, or custom epigenetic compute platforms.
FUSE, overlay filesystems, content-addressed storage, snapshotting, distributed caches, or object storage.
Agent runtimes, code interpreters, browser automation, remote development environments, or CI execution systems.
BYOC, private networking, customer-managed deployments, or enterprise security reviews.
Inngest, Temporal, Kafka, NATS, or other durable workflow and event systems.

Benefits
  • Fully covered health, dental, and vision insurance.
  • 401(k) plan.
  • Team lunches and dinners in the office.
  • Unlimited PTO.
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