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reView is a distributed graph-native analytics and reasoning platform built on a microservices architecture. At its core is a semantic execution and verification system that transforms ambiguous analytical questions into explainable, governed graph computations.Â
This role focuses on building backend systems that preserve semantic correctness across ingestion workflows, graph execution, distributed services, and analytical reasoning paths.Â
In our platform, correctness is not just whether an API returns a response. Correctness means:Â
graph relationships resolve to the intended entities,Â
traversals preserve the meaning of the underlying data,Â
derived computations remain explainable and reproducible,Â
distributed workflows maintain consistency under load and failure,Â
and analytical results are verifiably correct rather than merely plausible.Â
This is a backend and systems engineering role centered on graph execution, semantic reasoning infrastructure, distributed workflows, and correctness-oriented platform architecture.Â
The role is best suited for engineers who enjoy distributed systems, graph execution, query semantics, and correctness-oriented platform design.Â
ScopeÂ
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Backend and systems-focused engineering roleÂ
Design and evolution of semantic execution, graph validation, and reasoning infrastructureÂ
Close collaboration with platform, ingestion, and graph engineering teamsÂ
Containerized local development and shared staging environments for integration and execution validationÂ
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Leveling: At the mid level, you will implement and extend core platform behaviors and correctness mechanisms. At the senior level, you will shape execution semantics, system architecture, and how correctness is enforced across the platform.Â
Requirements
Semantic Execution & Backend SystemsÂ
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Design and implement backend services for graph execution and reasoning workflowsÂ
Build and optimize graph traversal, query planning, and computation behaviors over connected datasetsÂ
Develop validation and regression coverage for critical execution paths and service boundariesÂ
Contribute to execution semantics, identity resolution, and consistency guarantees across distributed workflowsÂ
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Execution & Workflow ValidationÂ
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Validate end-to-end platform flows (ingestion → graph → query → result)Â
Test distributed behavior under retries, partial failures, and asynchronous executionÂ
Ensure consistency and reproducibility across services and graph workflowsÂ
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Data & Graph ValidationÂ
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Verify correctness and consistency of node and relationship creation in Neo4j /Â MemgraphÂ
Design mechanisms that preserve identity, traversal correctness, and semantic consistency across ingestion and execution flowsÂ
Define and evolve graph test fixture strategies, including data seeding, isolation, and repeatabilityÂ
Performance & ReliabilityÂ
Run recurring load and stress tests against ingestion, graph execution, and query workflowsÂ
Identify and resolve bottlenecks across APIs, graph queries, and distributed execution pathsÂ
Collaborate with engineers on scaling behavior in Kubernetes environmentsÂ
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