Gyde - Infra Eng

Vault Talent•New York, NY

7d•Hybrid

About The Position

Gyde is building the first AI-native insurance brokerage platform. We acquire traditional brokerages and transform them into next-generation, data-driven organizations. Our platform helps agencies run more efficiently, serve clients more personally, and scale faster. We are looking for individuals excited to redefine how millions of people access and understand their healthcare coverage by building systems that turn unstructured data, human conversations, and fragmented processes into intelligence. You will build AI systems that improve healthcare access, design production-grade voice, chat, and predictive models for a highly regulated domain, and launch technologies that augment human judgment and make complex decisions transparent and scalable. The founding team has experience from Oscar, Stripe, Vista Equity Partners, and Bain & Company. Gyde has secured $60M in financing led by Lightspeed, with participation from Optum Ventures, Crystal Venture Partners, Virtue, MVP Ventures, and multiple endowment funds.

Requirements

Cloud & Kubernetes Foundations — Production EKS and AWS expressed in code, CI/CD you would stake a release on, and observability people actually act on. You have operated clusters through upgrades and incidents, not just deployed to them. Here this is table stakes rather than the whole job.
Application Engineering in a Shared Codebase — You write real TypeScript, not only glue. Durable workflows, relational data modeling, migrations, and packages other engineers import. You are comfortable opening a pull request in application code you do not own, and you know when a shared abstraction earns its keep.
Integration & Vendor Systems — You reverse-engineer an admin console rather than trusting its marketing page. You check plan tiers and API surfaces before committing to a design, and you can tell the difference between a control a system enforces and a process a human promises to follow.
Security, Compliance & Cost as Design Inputs — Least privilege is a default, not a cleanup task. You know where PHI leaks in a stack — logs, traces, metric labels, backups, third-party payloads — and you treat spend as something you instrument, not something finance discovers on an invoice.
Judgment, Sequencing & Written Decisions — You verify the premise before you build. You think in blast radius, carve-outs, and reversible-first rollout, because the first casualty of enforcing something early is usually a business process. You write the one-page decision doc with ranked options and open questions, and you can defend it to a non-engineer.
5–10 years in infrastructure, platform, SRE, or DevOps engineering, with meaningful production ownership.
Production Kubernetes experience — EKS preferred: cluster upgrades, autoscaling, networking, and hands-on troubleshooting.
Strong AWS fundamentals: IAM, VPC and networking, compute, storage, KMS, and a working grasp of the cost model.
Infrastructure as code in a real codebase — Pulumi preferred; Terraform or CDK acceptable with a willingness to work in Pulumi.
Production TypeScript or Node — you will ship application code in a shared monorepo, not only infrastructure definitions. We care that you have shipped real application code and will work primarily in TypeScript; which language you did it in matters less.
Relational data modeling and SQL, Postgres preferred; comfortable writing and reviewing migrations.
Built and owned CI/CD pipelines (GitHub Actions or comparable), including deployment strategy and rollback.
Observability in practice — metrics, logs, and distributed tracing, plus alerting that engineers trust.
Experience operating in a HIPAA, SOC 2, or otherwise regulated and audited environment.
A writing habit — design docs, RFCs, or postmortems you can point to.
Fluency with AI coding tools in day-to-day work — we are an AI-native company and expect engineers to use agents well.

Nice To Haves

Durable workflow engines — Temporal especially — or comparable orchestration and job systems.
Hands-on administration of an IdP or SaaS admin surface (Okta, Entra) including SCIM, RBAC, and API integration.
Multi-tenant SaaS, or M&A integration work folding acquired companies onto a single platform.
Data warehouse pipelines (Redshift, BigQuery, Snowflake) and event-ingestion plumbing.
LLM infrastructure: gateways and virtual keys, provider rate limits, token and spend telemetry.
Secrets management at scale, policy-as-code, and supply chain hygiene (image signing, SBOMs).

Responsibilities

Own the chain from problem to running control — take an ambiguous business or platform problem, establish what is actually true today rather than what the docs claim, design the fix, build it, and instrument it so you can prove it works. Most projects here cross the infra/app line and you own both sides.
Build in the monorepo — production TypeScript in shared packages other engineers import, Temporal workers and scheduled workflows, data models and SQL migrations, internal services and tooling. Not just YAML wrapped around someone else’s code.
Run the cloud platform — EKS, AWS defined in Pulumi, CI/CD, secrets and workload identity, and the metrics, logging, and alerting that tell us something is wrong before a broker does.
Evaluate and integrate the systems we buy — identity, orchestration, model gateways, warehouse and vendor APIs. Read a permission model and plan tier closely enough to know what a tool enforces versus what a person is merely promising to do, then build the glue that makes them agree.
Make security and compliance enforceable — least-privilege IAM and workload identity, BAA before PHI access, data classification, PHI-aware logs and metric labels, and audit trails that hold up in a carrier audit because the system produces them, not because someone remembered.
Own cost as an engineering surface — per-key LLM and infrastructure spend, estimated-versus-billed reconciliation, and alerting that fires before a runaway job becomes an invoice.