Senior Backend Engineer

Technoidentity

Posted 2mo ago

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Design and implement Temporal workflows, activities, and workers in Python
Model long-running, stateful processes as durable code
Own correctness under failure: idempotency, retries, timeouts, signals, queries, versioning, and safe deploys
Build and operate production Python backend services
Debug distributed-systems problems
Write high-quality, well-tested, well-typed code
Raise the bar in code review
Collaborate directly with client engineering teams
Defend design decisions in technical discussions

8+ Years experience
5+ years building production backend systems
Strong recent Python (3.10+): async/await, typing, packaging, testing discipline
Solid CS fundamentals — data structures, algorithms, complexity
Demonstrated distributed systems experience: concurrency, consistency, idempotency, message queues, at-least-once semantics, failure modes
System design ability: can design a scalable, fault-tolerant service end to end and reason about trade-offs
Production ownership: has run services in prod, handled on-call/incidents, and cares about observability (logs, metrics, tracing)
Strong written and verbal communication
Can work in ambiguity and move fast without breaking correctness
Legally authorized to work in the US
Hands-on with Temporal (or equivalents like Cadence, AWS Step Functions, durable workflow engines)
Understands the durable-execution model: determinism constraints, activity vs. workflow boundaries, signals/queries, durable timers, workflow versioning, worker scaling

Temporal-specific experience
Temporal certification, contributions, or having run Temporal at scale in prod
Clean, testable, idiomatic code and a high personal quality bar
Can decompose a vague, open-ended problem into a correct, incremental plan and explain reasoning clearly
Comfortable with performance work, profiling, and reasoning about systems under load
Genuine curiosity and fast learning
Track record of shipping reliable systems in fast-moving, high-stakes environments
Cloud (AWS/Google Cloud Platform)
Containers/Kubernetes
CI/CD
Datastores at scale (Postgres, Redis, Kafka, etc.)
Experience being embedded with or vendored into a demanding client engineering org

Skills