Senior/Staff Infrastructure Engineer

Hedra•San Francisco, CA

13d•Onsite

About The Position

As a Senior/Staff Infrastructure Engineer, you will own the reliability, availability, and operability of our core Python web services running at scale on AWS. You will be responsible for designing, maintaining, and improving the production infrastructure that keeps Hedra online: Kubernetes for orchestration, AWS as the core cloud platform, and Postgres on RDS as a key managed data service. Your work will focus on building a highly available runtime environment for our services, ensuring we can ship quickly while staying resilient through incidents, traffic spikes, and growth. You will design robust deployment patterns on Kubernetes, optimize our use of AWS (networking, load balancing, scaling, resilience), and put in place the observability and alerting we’re currently missing — from system-level metrics to product health signals. You’ll also partner with product engineers to make Python a great place to build: smoothing out CI/CD, runtime configuration, and production debugging. This is a hands-on infrastructure role, not a product feature role. You will work closely with engineering leadership and product teams, but your primary mandate is to keep our services healthy, observable, and ready to scale. We're looking for a full-time hire in our San Francisco office.

Requirements

At least 4+ years in infrastructure / SRE / platform / backend operations roles at technology companies
At least 3+ years running a critical Python web application in production on AWS
Strong experience operating services on Kubernetes, including: Designing deployment strategies (rolling, blue/green, canary) Autoscaling, resource limits/requests, capacity planning Debugging pod/node issues and cluster-level problems
Solid experience with AWS for high availability, such as: Multi-AZ architectures, load balancers, security groups, IAM basics Using managed services (RDS, S3, queues, caches, etc.) effectively Understanding maintenance windows, failure modes, and regional/AZ considerations
Experience improving observability for production systems: Implementing or refining system metrics (CPU, memory, disk, network, pod/node health) Adding application and product health metrics (latency, error rates, key business KPIs) Standing up useful dashboards, traces, structured logging, and actionable alerts
Comfort working with Python services at scale: CI/CD pipelines, dependency management, runtime configuration Performance tuning, concurrency models, and production debugging
Practical experience with Postgres on RDS: Running it reliably in production (backups, restores, monitoring, failover) Coordinating version upgrades and schema changes with minimal disruption
A developer experience mindset: Making it easier and safer for engineers to deploy and operate services Improving tooling, scripts, and workflows around our infrastructure and observability
A pragmatic approach to reliability and incident response: Participating in or leading on-call rotations and incidents Running postmortems, designing runbooks, and putting guardrails around risky operations
Strong communication skills and the ability to collaborate with product engineers and other stakeholders on tradeoffs between speed, reliability, and complexity

Responsibilities

Owning the reliability, availability, and operability of our core Python web services running at scale on AWS.
Designing, maintaining, and improving the production infrastructure that keeps Hedra online: Kubernetes for orchestration, AWS as the core cloud platform, and Postgres on RDS as a key managed data service.
Building a highly available runtime environment for our services, ensuring we can ship quickly while staying resilient through incidents, traffic spikes, and growth.
Designing robust deployment patterns on Kubernetes
Optimizing our use of AWS (networking, load balancing, scaling, resilience)
Putting in place the observability and alerting we’re currently missing — from system-level metrics to product health signals.
Partnering with product engineers to make Python a great place to build: smoothing out CI/CD, runtime configuration, and production debugging.
Keeping our services healthy, observable, and ready to scale.