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Requirements:
* Bachelor's degree in Supply Chain Management, Business Administration, or a related field.
* Minimum of 3 years of experience in production planning or supply chain management.
* Strong analytical skills and experience with production scheduling software.
* Excellent communication and interpersonal skills.
* Ability to work under pressure and manage multiple priorities.
* Proficiency in Microsoft Office Suite, particularly Excel.
* Experience in a manufacturing environment is preferred.

Requirements:
7+ years building production backend systems, including at least 2 years owning a distributed/async runtime (workflow engine, task queue, event-driven system, stream processor - Temporal.io, Celery, Kafka Streams, AWS Step Functions, or equivalent).
Deep hands-on Python (the player and workflow runtime are Python), plus working JavaScript.
Production scale experience and mindset. You've operated systems where throughput, tail latency, and blast radius are first-class design constraints, not afterthoughts.
Production experience operating self-hosted infrastructure on Kubernetes (EKS preferred). Comfortable reading helm charts, debugging pod resource issues, and reasoning about autoscaling.
Comfortable with CI/CD pipelines, infra-as-code, and being on-call for systems you ship.
AI fluency on both sides of the product. You use Claude Code or an equivalent agentic coding tool for real SDLC work (design docs, refactors, on-call triage) and have shipped LLM-backed features in production - agentic workflows, retrieval, tool-use, structured output, with an eval loop and a real opinion on latency, cost, and safety.
Strongly preferred (any one of these moves you up the stack):

Direct experience with Temporal.io in production - workflow versioning, replayer-based regression detection, signal/query/update patterns, codec authoring, per-namespace operational concerns.
Strong grasp of distributed-systems failure modes: idempotency, retries, timeouts, partial failures, non-determinism, exactly-once vs at-least-once semantics. You can debug a "stuck workflow" without a runbook.
Performance optimization in Python at the deserialization/interpreter / JIT layer (cython, mypyc, alternative JS engines, profiling tooling).
Operating modern self-hosted infrastructure at scale. Hands-on with multi-cluster EKS, a metrics + logs stack (Prometheus / Grafana / centralized log aggregation), IaC, and GitOps workflows. You've owned the dashboards and alerts you're on-call against - not just consumed someone else's.

Requirements:
At least 5 years of experience as a B2B SaaS Enterprise Software Product Manager in a leading web / SaaS product company, building amazing SaaS products - must
Significant experience in product management of Enterprise Software SaaS products for verticals such as insurance
Bachelor's degree in a relevant field, such as Computer Science
A solid understanding of web software and architectures
Excellent eye for UI and Customer Experience, and the supporting concepts and methods
Deep familiarity with the tools and methods of working with R&D and designers in an Agile environment
Excellent interpersonal, communication, and presentation skills
Intelligence, curiosity, and out-of-the-box thinking when identifying market opportunities and solving customer problems
Stay current with AI advancements and think creatively about how to leverage AI in your product area