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Accenture

Advises businesses and runs their technology

Tech Delivery Subject Matter Expert

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A minimum of 5 years of experience is required.
  • 15 years of full-time education is required.
  • Strong hands-on expertise in SAP SuccessFactors technical integrations, including design, build, troubleshooting, and operations.
  • Solid understanding of enterprise integration fundamentals, including APIs, payload formats, transformations, scheduling, eventing, secure transport, and monitoring.
  • Hands-on capability with LLM-integrated workflows, including tool-calling orchestration, retrieval-grounding, prompts and templates, and evaluation harnesses.
  • Engineering discipline in clean implementation, automated testing, CI/CD, and production reliability practices.

Responsibilities

  • Drive innovative practices into delivery and bring depth of expertise to delivery engagements.
  • Apply technical expertise and business acumen in a trusted-advisor relationship with clients to gather requirements and analyze, design, and/or implement technology best-practice business changes.
  • Design and implement end-to-end SuccessFactors integrations across HR domains, including employee lifecycle, organizational data, onboarding, learning, recruiting, and payroll-adjacent flows.
  • Build and support integrations using API-based, file-based, event-triggered, and scheduled or batch approaches aligned with enterprise integration patterns.
  • Define integration blueprints, including interface contracts, payload schemas, transformations, error handling, retries, and reconciliation approaches.
  • Engineer integrations between SuccessFactors and enterprise systems, including ERP, payroll, identity and access, finance, time systems, third-party HR applications, and data platforms.
  • Build middleware orchestrations using routing, transformation, enrichment, correlation IDs, secure connectivity, and throttling.
  • Enable secure transport patterns such as SFTP and HTTPS, credential management, certificate handling, and environment promotion across landscapes.
  • Implement event-driven integration approaches for employee and organizational changes, ensuring system consistency with minimal latency and controlled data distribution.
  • Establish canonical data modeling and semantic mapping practices to reduce duplication, minimize point-to-point sprawl, and improve maintainability.
  • Drive data minimization and privacy-aware integration design by sharing only the data needed where it is needed.
  • Build integration agents that interpret integration intent, generate or validate mappings, and propose transformation logic using tool-based orchestration, including schema tools, metadata tools, and test harnesses.
  • Implement retrieval-grounded integration assistance that retrieves interface specifications, mapping rules, runbooks, and past incident patterns to produce grounded outputs.
  • Create conversational integration operations experiences for troubleshooting, guided remediation, automated log summarization, and impact analysis, backed by verifiable evidence.
  • Build automated integration testing strategies, including contract tests, schema validation, payload regression suites, replay testing, and environment parity checks.
  • Implement offline and online evaluation loops for AI behaviors, including golden test sets for mappings and transformations, hallucination checks, grounding rates, and safety regressions.
  • Define release gates for integration changes and AI prompt or tool updates to prevent silent production degradation.
  • Establish observability for integrations and AI components through structured logs, traces, metrics, correlation, and alerting across the integration chain.
  • Engineer failure-mode handling, including retries, fallbacks, circuit breakers, dead-letter queues or error queues, and reconciliation dashboards.
  • Build AI-assisted incident response patterns for triage, root-cause clustering, and remediation recommendations, with strict access controls and human-in-the-loop confirmations.
  • Enforce enterprise governance for data privacy, authorization boundaries, and least-privilege access, especially for sensitive HR attributes.
  • Implement responsible AI guardrails for integration agents, including tool permissions, action boundaries, redaction rules, and approval workflows for high-risk operations.
  • Maintain auditability across integration actions and AI-generated decisions, recording who, what, why, and when for compliance needs.

Desired Qualifications

  • Experience with integration middleware and iFlow-style orchestration patterns.
  • HR domain familiarity with employee master data, organizational structures, time and absence, onboarding, learning, recruiting, and payroll-adjacent data flows.
  • Data modeling practices for canonical HR entities and semantic consistency across systems.
  • Experience with secrets management, certificate lifecycle management, and enterprise security controls in integration landscapes.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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