Software Engr. -AI, SAP Commerce & Durable Orchestration

Voto Consulting LLC
United States
14 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) JavaScript (Programming Language) Artificial Intelligence Amazon Web Services Automation of Tests Microsoft Azure Software Debugging Software Tools SAP (Applications) TypeScript Management of Software Versions ReactJS
+4 more
Prompt Engineering Kubernetes Apache Kafka Hybris

Job description

  • We are seeking a Senior Software Engineer to modernize a large SAP Commerce Cloud platform through AI-assisted engineering, context engineering, and durable workflow orchestration.
  • A central responsibility of this role is designing business processes that remain reliable across service failures, deployments, retries, and long execution periods.
  • The engineer should understand Temporal-style programming models and be able to apply the same principles using Temporal, Cadence, Azure Durable Functions, Conductor, or a comparable platform.
  • This is a hands-on engineering role-not an AI strategy or prompt-engineering position.

Requirements

  • Senior-level experience delivering distributed production systems.

  • Strong SAP Commerce Cloud/Hybris or similar platform development experience.

  • Advanced Java and Spring development skills.

  • Experience with React.js and modern JavaScript or TypeScript.

  • Hands-on experience with at least one durable orchestration platform, such as Temporal, Cadence, Azure Durable Functions, AWS Step Functions, or Conductor.

Strong understanding of:

  • Workflow determinism and replay
  • Workflow versus activity responsibilities
  • At-least-once execution semantics
  • Idempotency and duplicate prevention
  • Retry classification and non-retryable failures
  • Compensation and saga patterns
  • Durable timers and asynchronous events
  • Workflow versioning and backward compatibility
  • Failure recovery and operational visibility

  • Experience designing event-driven integrations using Kafka or comparable messaging technology.
  • Demonstrated use of AI coding assistants or agentic engineering tools on substantive software work.
  • Practical understanding of context engineering: equipping AI systems with appropriate domain knowledge, tools, instructions, examples, and validation.

Strong automated testing, debugging, performance-analysis, and production-support skills.

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