About the TeamThe
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 RoleDecagon 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.
BenefitsWe 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.
