Job at Nomic AI
Senior Platform Engineer
- Employer
- Nomic AI
- Location
- New York HQ
- Workplace
- hybrid
- Employment
- full-time
- Department
- Engineering
- Last published
- First listed on USASI
Apply on Nomic AI’s site (external site)View the posting on Nomic AI’s job board (external site)
This posting comes from Nomic AI’s own Ashby job board. USASI checks that board twice a day and removes this page once the employer closes the posting. The description below is Nomic AI’s text as published; USASI does not edit it, does not recruit, and does not take applications. How jobs are collected.
Job description
About Nomic
Nomic is the domain-specific AI platform for the Architecture, Engineering, and Construction (AEC) industry. We help enterprise teams extract structured knowledge from decades of drawings, specs, and project files — combining embedding models, document parsing, and autonomous agents that reason over real-world data and take action in live environments.
The Role
Nomic is hiring a Senior Platform Engineer to own our infrastructure stack — multi-account AWS, Kubernetes, IaC, CI/CD — and the systems that make our agents run well in production: orchestrating rollouts across customer environments, keeping inference fast and reliable, and maintaining industry-leading performance as we scale.
We're already deployed across dozens of companies on three continents, delivering value in production today, and we train and deploy our own models. Your job will be to scale that footprint up dramatically — more customers, more environments, more inference — without performance or reliability slipping as we grow.
This is a senior IC role with broad ownership and real architectural influence. You'll have a wide surface area and the autonomy to shape it.
What You'll Own
Rollout and deployment. Orchestrating how our agents and services roll out across many customer cloud environments: deployment strategies, per-customer configuration, automated health checks, and the monitoring that catches problems before customers do.
Inference and performance. Keeping model inference fast, reliable, and cost-effective at scale — serving infrastructure, GPU workloads, and the performance work that keeps agents responsive as volume grows.
Core infrastructure. Kubernetes, multi-account AWS, CI/CD, observability (traces, metrics, logs, alerting, SLOs), disaster recovery, and cost management.
Security posture. Access controls, secrets management, network security, image scanning, dependency auditing, and compliance work (SOC 2, enterprise security) as customer requirements demand.
Infrastructure as code. Defining, provisioning, and evolving all infrastructure through code — designing modules, managing state, and thinking hard about blast radius.
About You
Required
- 5+ years in infrastructure, DevOps, or SRE roles running cloud infrastructure in production
- Strong Kubernetes experience — deploying workloads, debugging real issues, working with operators and controllers
- Solid infrastructure-as-code skills — designing modules, managing state, reasoning about blast radius
- Strong software engineering fundamentals — you write and review production code in Python and/or TypeScript, not just infra configs
- Linux systems and networking fundamentals
- CI/CD pipeline design and maintenance
- A proactive orientation and genuine comfort owning a wide surface area
Preferred
- Terraform experience
- Observability platforms (Datadog, OpenTelemetry) — dashboards, trace/metric/log pipelines
- PostgreSQL operations — performance tuning, replica management
- ML/AI infrastructure — inference services, GPU workloads, model serving, eval pipelines
- Multi-tenant deployment patterns or per-customer isolation
- Experience building sandboxed execution environments or automated reliability systems
What We Offer
- Competitive base salary and performance-based compensation
- Equity participation
- Medical, dental, and vision coverage
- Flexible PTO
- Hybrid NYC model preferred, remote considered for the right person
- A senior role with broad ownership — the infrastructure decisions you make define how reliably Nomic runs and scales in the field
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