Engineering Manager, Platform Infrastructure

Decagon•San Francisco, CA

2d•Onsite

About The Position

Decagon is seeking a hands-on Engineering Manager to lead the Platform team. This is a deeply technical player/coach role responsible for the compute, networking, CI/CD, and deployment systems that underpin all of Decagon's engineering efforts. The role involves managing a team responsible for multi-cloud SaaS environments as well as single-tenant VPC and on-prem deployments for regulated enterprise customers. The manager will stay close to the code, review designs, participate in incident response, and contribute directly when needed. A key aspect of the role is leading by example in AI-assisted engineering, setting standards for the team's use of AI coding tools to improve quality and speed. The position requires strong people leadership, execution across concurrent enterprise commitments, and technical depth for architectural decisions under constraints. The Platform team builds and operates the foundations for Decagon, including platform, model inference, compute, data, and developer experience, partnering with product, research, and applied AI teams to deliver high-scale, low-latency systems.

Requirements

2+ years of engineering management experience leading high-performing infrastructure, platform, or SRE teams in fast-moving environments, with a strong IC background before that.
Deep technical depth across infrastructure — you can design, review, and when needed, build core systems in compute, networking, CI/CD, or deployment orchestration. You're comfortable dropping into the codebase and shipping a PR.
Hands-on experience with cloud platforms (AWS, GCP, or Azure), Kubernetes, infrastructure-as-code (Terraform or similar), and modern CI/CD systems.
A track record of delivering multi-quarter infrastructure initiatives — migrations, platform rebuilds, or capability launches — through ambiguity, creating clarity for your team and stakeholders.
A strong point of view on AI-assisted engineering: you actively use AI coding tools yourself, have opinions on where they work and where they don't, and see it as a core part of how modern infrastructure teams should operate.
Care deeply about engineering craft and operational excellence, including reliability engineering, observability, incident learning, and cost discipline.
Communicate clearly and collaborate well across Security, Product Engineering, and customer-facing functions.

Nice To Haves

Experience delivering on-premises, air-gapped, or single-tenant deployments for regulated enterprise customers (financial services, healthcare, government).
Experience with multi-cloud or cloud-to-cloud migrations at scale.
Background in security and compliance frameworks (SOC 2, PCI DSS, FedRAMP, or similar).
Experience building developer platforms or paved-path systems that meaningfully raised engineering velocity.
Experience building internal tooling, agents, or workflows that use LLMs to accelerate engineering work.

Responsibilities

Build, lead, and develop a high-performing team of infrastructure engineers, including hiring, coaching, and performance management.
Own the technical strategy and roadmap for Decagon's Platform — compute, networking, CI/CD, IaC, and the deployment systems that underpin both SaaS and enterprise environments.
Stay hands-on: review designs and PRs with depth, lead architecture for hard problems, and contribute code directly when the team needs it — whether that's a critical migration, an on-call escalation, or an enterprise deployment under time pressure.
Drive architecture for multi-cloud and on-prem/cloud-prem deployments, including single-tenant VPC topologies, private connectivity, and air-gapped environments for regulated customers.
Set reliability, security, and cost standards across the platform, and build an operating cadence (on-call, incident review, capacity planning) that prevents repeated incidents and keeps the platform healthy as we scale.
Invest in developer experience — paved paths, golden templates, and CI/CD systems that let product teams ship quickly without compromising safety or consistency.
Raise the bar on AI-assisted engineering: define how your team uses AI coding tools, agents, and internal tooling to deliver faster with higher quality, and build the workflows, evals, and guardrails that make this durable.
Partner with Security, Product Engineering, and customer-facing teams to deliver enterprise deployments on aggressive timelines, navigate compliance requirements, and translate customer constraints into durable platform capabilities.