Kubernetes Jobs in Web3

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Job Position Company Posted Location Salary Tags

Dvtrading

Remote

$36k - $45k

Newton

Toronto, Canada

$73k - $110k

PURVIEW

San Francisco, CA, United States

$98k - $100k

Zinnia

Remote

$82k - $110k

Okx

Remote

$126k - $131k

Polygon Labs

United Kingdom

$84k - $109k

Chainlink Labs

United States

$115k - $117k

Alpaca

Remote

$129k - $186k

Logos

Remote

$84k - $150k

Saga

Los Altos

$98k - $112k

Binance

Bangkok, Thailand

Impossible Cloud

New York, NY, United States

$127k - $177k

Coin Market Cap Ltd

Taipei, Taiwan

$84k - $100k

Zscaler

Remote

$126k - $131k

Zscaler

Remote

$91k - $153k

Dvtrading
$36k - $45k estimated
Remote

About Us:Founded more than 15 years ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 450 people operating throughout North America and in Europe. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users. Now, DV group affiliates include two broker dealers, a cryptocurrency market making firm, and a bourgeoning investment adviser. Role Overview:This is a project-focused internship for an AI engineer embedded on the DevOps team. You will report to the DevOps lead and partner with internal technology teams. The work centers on internal, production-adjacent tooling—not training or shipping customer-facing ML models.Core Internship Projects:

Generative assistant for alert response

Learn our observability stack and what data exists today e.g. Prometheus, Grafana, Loki, Tempo, Alertmanager, OpenTelemetry. Prototype a generative agent that uses approved observability sources to propose structured mitigation suggestions for alerts (hypothesis, checks, likely causes, safe next steps), with traceability back to queries, dashboards, or signals where possible.

Retrieval on internal data (RAG)

Build and iterate on RAG over permissioned internal data sources (e.g. runbooks, tickets, docs, system design, network design, postmortems) so suggestions and Q&A are grounded and citeable. Work with teams to improve coverage and quality of that corpus (metadata, ownership, freshness).

Path toward agentic remediation (design + scoped implementation)

Outline how the system could execute approved remediations behind explicit guardrails and human approval. Implement only what is allowed and under review—no autonomous production changes without platform sign-off.

Broader internal Q&A

Explore how additional internal, permissioned firm data can support natural language questions for engineers. Across all phases, permissioning, auditing, logging, and cost controls are non-negotiable requirements, not stretch goals.

Responsibilities:

Design and prototype agent workflows with tool use, policy boundaries, and human-in-the-loop where appropriate. Collaborate with platform and service teams to make more observability and operational context available in a safe, governed way for agents. Document experiments, limitations, evaluation approach, and safety assumptions; ship changes via Git (branches, merge requests, meaningful commits).

Requirements:

Pursuing a BS or MS in Computer Science, Computer Engineering, Information Systems, or a related field; expected graduation Summer 2026 or 2027. Hands-on experience using AI tools (e.g. LLM APIs, assistants, or coding agents) in real projects; preferably experience building an agent (tools, orchestration, or similar—not only prompt-only chat). Experience with RAG (retrieval design, chunking, evaluation, grounding, or production-minded prototyping)—including applying it to real or simulated internal/knowledge-base >

Preferred Skills:

Linux fundamentals (shell, processes, logs, permissions, basic troubleshooting). Networking basics: DNS, TCP/HTTP/S, ports, load balancing vs Ingress at a conceptual level. Kubernetes fundamentals: debugging, pods, services, ingress Coursework or projects involving Kubernetes, Prometheus/Grafana, OpenTelemetry, CI/CD, Terraform/Ansible, or cloud (AWS/GCP/Azure).

Compensation range: $30.00-$35.00/hr DV is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with DV should submit resumes in response to DV’s posted positions. All resumes submitted by search firms to DV via e-mail, the Internet, personal delivery, facsimile, or any other method without a valid written agreement shall be deemed the sole property of DV, and no fee will be paid in the event the candidate is hired by DV. DV is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.  

Is Kubernetes high demand?

Yes, Kubernetes is currently in high demand in the technology industry

Kubernetes is an open-source container orchestration platform that is widely used for deploying, scaling, and managing containerized applications

It provides a standardized way to manage and automate the deployment of containerized applications across multiple hosts and provides benefits such as reliability, scalability, and flexibility

As more and more organizations move towards containerized architectures, Kubernetes has become a critical component of their infrastructure

Kubernetes is used by companies of all sizes, from startups to large enterprises, and across various industries, including finance, healthcare, and e-commerce

According to various job market and salary surveys, Kubernetes-related skills are in high demand, and job positions related to Kubernetes are growing at a rapid pace

In fact, Kubernetes is often listed as one of the top skills that are in high demand by technology companies

Overall, Kubernetes is a highly sought-after skill in the technology industry, and it's likely to remain in high demand in the foreseeable future as more and more organizations adopt containerization and cloud-native architectures.