Level

Decagon

Senior Software Engineer, Cloud Infrastructure

Decagon is hiring a Senior Software Engineer, Cloud Infrastructure in San Francisco, United States. It pays $200k-$400k a year and Level rates it ; you can apply on Decagon.

Level's read on this job

  • Level rates this software engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Pay on this posting starts 19% higher than the typical software engineer posting on Level.
  • The posting mentions Kubernetes, Docker and CI/CD among its tools and skills.
  • Level classes it as a senior role.
  • Decagon has 133 other open roles on Level.

AI in this role

Senior Software Engineer to build and operate cloud infrastructure and ML serving platforms for conversational AI agents.

kubernetesdockerci-cd
ai-agentscloud-infrastructureml-servingdevopssecurityreliability

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.

Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.

We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.

About the Team

The Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.

Read more about the infra team's work here: https://decagon.ai/blog/what-an-air-gapped-ai-deployment-actually-requires

About the Role

Decagon builds agentic AI that resolves customer support conversations end to end, for companies ranging from fast-growing startups to some of the largest financial institutions in the world. Keeping that system fast, reliable, and secure (across our multi-tenant cloud and inside customers' own locked-down environments) is an infrastructure problem, and that's the problem this role owns.

You'll build the platforms and abstractions our product teams ship on, and you'll architect and operate the deployments that run our agents inside enterprise customer clouds, where security, compliance, and operational rigor matter as much as speed. The work is core infrastructure at heart: reliability, CI/CD, deployment automation, on-call. You'll be joining a team with real infrastructure and momentum already in place, but there's no established playbook for running agentic systems at this scale, so a big part of the job is figuring it out as the technology shifts and usage grows by orders of magnitude.

What you'll do

  • Build the platform

    • Design the development and production platforms that power our products, and the abstractions over cloud infrastructure, Kubernetes, and networking that let engineers ship without becoming infrastructure experts.

    • Make sure it all scales to the next order of magnitude as usage grows.

  • Own enterprise deployments

    • Take end-to-end ownership of deployment architecture in customer-owned cloud environments (VPC configuration, permissioning, networking, provisioning) and the full lifecycle that follows: setup, upgrades, scaling, and incident support.

    • Build the runbooks and automation that make it repeatable.

  • Keep agentic workloads reliable

    • Treat monitoring, alerting, and rollback as first-class parts of anything you ship, not afterthoughts.

    • Own the reliability of the systems our AI agents depend on in production, where latency, availability, and graceful degradation directly shape the customer experience.

  • Partner across boundaries

    • Work directly with customers' platform, security, and DevOps teams to navigate their infrastructure and compliance constraints, and with our Product, Security, Sales, and Customer Success teams to turn customer requirements into concrete deployment plans.

Your background looks something like this

  • 4+ years building and operating core infrastructure, platform engineering, or infrastructure/DevOps, ideally with some customer-facing deployment experience.

  • Deep experience with a major cloud provider (GCP, AWS, or Azure), along with Terraform and Kubernetes at scale.

  • Strong grasp of cloud networking fundamentals (VPCs, IAM, DNS, load balancing) and how they surface as real deployment constraints.

  • A track record operating production systems reliably: monitoring, on-call, incident response, and reasoning about failure modes up front.

  • Comfort navigating ambiguity across a range of stakeholders, from engineers to security and compliance teams, and turning those conversations into actionable plans.

  • Clear technical writing and a track record of driving adoption across teams.

  • Comfortable in a fast-moving environment with rapid change.

Even better if you have

  • Experience managing deployments in customer-owned cloud environments, including security reviews, compliance requirements, and change management.

  • Experience building internal platforms or paved roads: service templates, self-serve environments, CI/CD pipeline design, deployment automation.

  • Familiarity with observability and incident management in distributed systems (Prometheus, Grafana, Datadog, or similar).

  • Infrastructure-as-code with a security-minded approach to supply chain (provenance, secrets, least privilege).

  • Experience operating latency-sensitive or ML/AI-serving workloads in production.

  • Experience using AI-assisted tooling to make yourself and your team dramatically more effective.

Compensation

$200K – $400K + Offers Equity

This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.

In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.

Benefits

We proudly offer the following benefits for our full-time employees:

  • Medical, Dental, and Vision benefits for you and your family

  • Life Insurance and Disability Benefits

  • Retirement Plan (e.g., 401K, pension)

  • Parental Leave

  • Fertility and family building benefits through Carrot

  • Monthly stipend to support your wellness, lifestyle, and work-life balance

  • Daily lunches and snacks in the office to keep you at your best

  • Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)

These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

How we rate this

Senior Software Engineer, Cloud Infrastructure at Decagon rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsCloud InfrastructureML ServingDevOpsSecurityReliabilityKubernetesDocker

Also common in software engineer jobs at this level

Pay

This job starts at
$200k
Typical software engineer job
$168k

This posting starts 19% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a project where cloud infrastructure was part of your work. What did you do?
  3. Tell me about a project where ml serving was part of your work. What did you do?
  4. Tell me about a project where devops was part of your work. What did you do?
  5. Tell me about a project where security was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, Cloud Infrastructure, ML Serving, DevOps, and Security. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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