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Artos AI

Technical Solutions Engineer

Posted 3 Months Ago
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Hybrid
San Francisco, CA, USA
167K-231K Annually
Mid level
Hybrid
San Francisco, CA, USA
167K-231K Annually
Mid level
Serve as the primary technical contact for enterprise customers deploying Artos (cloud or BYOC). Install, configure, troubleshoot, and scale deployments; diagnose issues through logs, infrastructure, and code; escalate to engineering. Own customer-facing and security/compliance documentation. Collaborate with engineering, implementation, and customer success to improve product reliability and deployment experience.
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About Artos:

At Artos, we build tools that help biopharma companies create and manage their R&D documentation in a fraction of the time. If you’re looking to join a team whose mission is to fundamentally change the way that drug development gets done, we’d love to talk to you.


The Role:

We’re looking for a Technical Solutions Engineer who brings a strong mix of DevOps, software engineering, and customer-facing skills to help customers deploy, operate, and scale Artos.

You’ll troubleshoot across the full stack, from Kubernetes, cloud infrastructure, networking, and deployment configuration to the Artos platform itself. When something breaks, you’ll determine whether the problem lives in the customer’s environment, our application, or somewhere in between, then dig into the logs, configuration, infrastructure, and code to find the root cause.

You’ll work directly with customer engineering teams while partnering closely with Artos Engineering to reproduce issues, resolve bugs, and improve the reliability and supportability of the platform.

This is a great fit for someone who enjoys moving between infrastructure and application-level debugging and is equally comfortable working directly with customers to solve complex technical problems.

What You’ll Do:
  • Lead technical deployments of Artos into customer-managed AWS, Azure, and GCP environments.

  • Configure and troubleshoot Kubernetes, containers, networking, IAM, authentication, secrets, and other deployment dependencies.

  • Diagnose issues across customer infrastructure, Artos application services, APIs, integrations, and application behavior.

  • Use logs, metrics, traces, and code-level debugging to isolate root causes and drive issues through resolution.

  • Reproduce application issues, investigate bugs, contribute to bug reports, validate fixes, and partner with Artos Engineering on resolution.

  • Build and maintain deployment automation and infrastructure-as-code using Terraform and related tooling.

  • Partner directly with customer DevOps, infrastructure, engineering, and security teams throughout deployment and ongoing operation.

  • Improve CI/CD workflows, monitoring, observability, and operational tooling that make Artos easier to deploy and support.

  • Own customer-facing technical documentation, including installation and deployment guides, architecture documentation, runbooks, and security review materials.

What We’re Looking For:
  • 5+ years of experience in solutions engineering, DevOps, SRE, platform engineering, software engineering, cloud infrastructure, or a similar technical role.

  • Strong hands-on experience with Kubernetes, Docker, Terraform, and cloud infrastructure.

  • Experience deploying and supporting production applications on AWS, Azure, or GCP.

  • Software engineering skills and the ability to debug application-level issues rather than treating the application as a black box.

  • Ability to work with and troubleshoot APIs, application services, integrations, logs, and distributed systems.

  • Ability to write and debug code or automation using TypeScript, Python, Bash, or similar languages.

  • Strong understanding of networking, IAM, authentication, secrets management, and cloud security fundamentals.

  • Familiarity with CI/CD, monitoring, logging, and observability tooling.

  • Strong communication skills and experience working directly with customer engineering teams.

  • Ability to independently take ambiguous technical problems from initial customer report through root cause and resolution.

Nice to Have:
  • Experience with BYOC, self-hosted, or private-cloud deployments.

  • Experience supporting technical enterprise SaaS products.

  • Experience with Helm, Datadog, Grafana, Prometheus, or similar tooling.

  • Experience investigating or fixing bugs in a production software codebase.

  • Experience with enterprise security or compliance reviews.

  • Familiarity with AI/LLM infrastructure or ML platforms.

  • Experience in life sciences, healthcare, or another regulated industry.


Other Information:

Very comfortable working in a fast-paced and intense startup environment

Willing to work in-person in our office in Mission Bay 4-5 days/week

Likes matcha KitKats, believes every LLM prompt is just Schrödinger’s cat waiting to be observed, and knows too many random facts about the Mongol postal system

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