The ad says“Experience using agentic coding tools and workflows beyond basic prompting”
The ad says“Experience with CI/CD, comprehensive testing and validation strategies, monitoring, alerting, and production operations”
The ad says“Strong programming fundamentals and experience working in systems-oriented backend languages. Python experience is helpful given our stack”
The ad says“Strong distributed systems fundamentals, including experience reasoning about concurrency, queues, retries, failure recovery, consistency, backpressure, capacity, and system behavior under load”
The ad says“Experience with CI/CD, comprehensive testing and validation strategies, monitoring, alerting, and production operations”
The ad says“Strong distributed systems fundamentals, including experience reasoning about concurrency, queues, retries, failure recovery, consistency, backpressure, capacity, and system behavior under load”
The ad says“Strong distributed systems fundamentals, including experience reasoning about concurrency, queues, retries, failure recovery, consistency, backpressure, capacity, and system behavior under load”
The ad says“5+ years of software engineering experience, with significant experience building distributed backend or infrastructure systems”
The ad says“Strong distributed systems fundamentals, including experience reasoning about concurrency, queues, retries, failure recovery, consistency, backpressure, capacity, and system behavior under load”
The ad says“Experience with CI/CD, comprehensive testing and validation strategies, monitoring, alerting, and production operations”
The ad says“Strong distributed systems fundamentals, including experience reasoning about concurrency, queues, retries, failure recovery, consistency, backpressure, capacity, and system behavior under load”
The ad says“Strong distributed systems fundamentals, including experience reasoning about concurrency, queues, retries, failure recovery, consistency, backpressure, capacity, and system behavior under load”
Values
The ad says“Compute scheduling, orchestration, or resource management”
The ad says“GPU or accelerator infrastructure”
The ad says“Experience with inference or model-serving infrastructure”
The ad says“Kubernetes or other cluster orchestration systems”
The ad says“Performance optimization and profiling”
The ad says“Developer infrastructure, APIs, SDKs, or platform engineering”
The ad says“Strong programming fundamentals and experience working in systems-oriented backend languages. Python experience is helpful given our stack”
We’re looking for a Senior or Staff Software Engineer with deep experience building and operating distributed production systems
You’ll work on the infrastructure underlying Hedra’s inference platform: systems that schedule and route compute, serve models efficiently, handle high-throughput workloads, and remain reliable as both traffic and the number of models we support grow
The problems are often ambiguous and don’t have obvious answers. We’re looking for someone who can reason from first principles, identify bottlenecks and failure modes before they become problems, and make thoughtful tradeoffs across performance, reliability, complexity, and cost
Design, build, and operate distributed systems that power Hedra’s inference infrastructure
Build systems for scheduling, routing, and managing compute-intensive workloads across heterogeneous resources
Improve throughput, latency, reliability, and resource utilization across our serving infrastructure
Design systems that remain predictable and resilient under load, partial failures, changing capacity, and unpredictable workloads
Own production systems end to end, including deployment, CI/CD, testing and validation, observability, monitoring, alerting, debugging, and incident response
Identify architectural bottlenecks and failure modes and drive solutions rather than waiting for problems to be fully specified
Work across infrastructure, model serving, APIs, and developer-facing systems as the platform evolves
Use modern agentic coding workflows as part of how you design, build, debug, and ship software
Help shape the technical direction of a small engineering organization where individual engineers have substantial ownership
Benefits
Healthcare (Silver PPO Medical, Vision, Dental)
401k (no match)
Gym access (at our office)
Equity
Preferred experience
You do not need to come from an AI company or already be an expert in model inference. We care much more about depth in distributed systems and your ability to apply that experience to a new problem space
Strong judgment around architectural tradeoffs, particularly reliability, performance, complexity, and operational cost
5+ years of software engineering experience, with significant experience building distributed backend or infrastructure systems
Strong programming fundamentals and experience working in systems-oriented backend languages. Python experience is helpful given our stack
A track record of designing and operating high-availability production services at meaningful scale
Experience using agentic coding tools and workflows beyond basic prompting
Experience debugging complex production systems across multiple layers of the stack
Experience with CI/CD, comprehensive testing and validation strategies, monitoring, alerting, and production operations
Strong distributed systems fundamentals, including experience reasoning about concurrency, queues, retries, failure recovery, consistency, backpressure, capacity, and system behavior under load
Ability to communicate technical decisions clearly and collaborate with engineers across infrastructure, research, and product
Comfort operating in an environment where problems are often underspecified and engineers are expected to independently determine the right approach
GPU or accelerator infrastructure
Experience with inference or model-serving infrastructure
Compute scheduling, orchestration, or resource management
High-throughput or low-latency systems
Kubernetes or other cluster orchestration systems
Performance optimization and profiling
Experience operating infrastructure across cloud and/or bare-metal environments
Developer infrastructure, APIs, SDKs, or platform engineering