Senior Software Engineer - AI, SAP Commerce & Durable Workflows

Job Title: Senior Software Engineer - AI, SAP Commerce & Durable Orchestration Location: Remote (USA) Role Overview: 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.