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.
Responsibilities
- Develop and support SAP Commerce Cloud capabilities using Java and Spring.
- Build Integrations with OCC and REST APIs.
- Design durable workflows for long-running commerce processes such as commerce cart work flows, order orchestration, inventory updates, and recovery operations.
- Separate deterministic orchestration logic from side-effecting activities.
- Design workflows that support:
- Durable state and event-history replay
- Automatic retries and configurable backoff
- Idempotent activity execution
- Timeouts, timers, and cancellation
- Compensation and business rollback
- Signals, events, and external callbacks
- Human-in-the-loop processing
- Workflow queries and operational visibility
- Versioning of workflows already in production
- Safe recovery after worker or dependency failure
- Establish meaningful workflow identifiers, task queues, concurrency limits, and rate controls.
- Prevent unbounded workflow histories through appropriate continuation and lifecycle strategies.
- Build automated workflow, activity, replay, integration, and failure-path tests.
- Integrate durable workflows with SAP Commerce, Kafka, APIs, databases, and external services.
- Apply AI and context engineering to code discovery, implementation, testing, documentation, incident response, and release analysis.
- Build reusable AI instructions, agent skills, MCP integrations, repository context, and verification guardrails.
- Diagnose SAP Commerce performance issues involving FlexibleSearch, persistence, caching, TaskEngine, Kafka consumers, and database contention.
Required Qualifications
- 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.
Preferred Qualifications
- Temporal Java SDK experience.
- Experience operating Temporal workers, task queues, namespaces, schedules, search attributes, signals, queries, and updates.
- Experience testing workflow replay and safely evolving active workflow definitions.
- Knowledge of Protobuf, schema evolution, and backward-compatible contracts.
- SAP Commerce 2211, Java 21, and Spring 6 experience.
- Experience with OpenTelemetry, Dynatrace, Kubernetes, Azure, and centralized logging.
- Experience building AI agents, MCP servers, reusable agent skills, or retrieval-augmented development systems.
What Success Looks Like
- Commerce processes continue reliably through deployments, outages, and transient dependency failures.
- Workflow retries do not create duplicate payments, orders, inventory changes, or external requests.
- Long-running processes are observable, queryable, testable, and recoverable.
- Existing workflows can evolve without replay failures or breaking in-flight executions.
- AI-assisted engineering measurably improves delivery while preserving testing, review, and human accountability.
- SAP Commerce performance, operational toil, and release risk decrease over time.
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