Note: The job is a remote job and is open to candidates in USA. Technoidentity is a Data+AI product engineering company building cutting-edge solutions in the FinTech domain. The Senior Backend Engineer will build durable, long-running backend systems on Temporal for Tier-1 clients, focusing on transaction-critical workflows and ensuring reliability and correctness.
Responsibilities
- Design and implement Temporal workflows, activities, and workers in Python — modeling long-running, stateful processes (orchestration, sagas, human-in-the-loop, exception handling) as durable code
- Own correctness under failure: idempotency, retries, timeouts, signals, queries, versioning, and safe deploys of in-flight workflows
- Build and operate production Python backend services — APIs, async I/O, data access, integration with queues and datastores
- Debug distributed-systems problems: race conditions, partial failures, non-determinism, replay mismatches
- Write high-quality, well-tested, well-typed code and raise the bar in code review
- Collaborate directly with client engineering teams and defend design decisions in technical discussions
Skills
- 5+ years building production backend systems, with strong recent Python (3.10+): async/await, typing, packaging, testing discipline
- Solid CS fundamentals — data structures, algorithms, complexity — strong enough to pass a rigorous coding interview loop
- 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 out loud
- 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
- Bonus: Temporal certification, contributions, or having run Temporal at scale in prod
- 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
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