Director of Software Engineering Workforce ExperienceTechnology

If you are a software engineering leader ready to take the reins and drive impact weve got an opportunity just for you.

Job Responsibilities

• Set engineering vision and roadmap execution for the Talent Performance platform balancing user experience time-to-market reliability and control obligations.
• Lead multiple cross-functional engineering teams (full stack backend platform/integration SRE/operations as applicable) including org design hiring coaching performance management and succession planning.
• Drive platform architecture and modernization including cloud-native patterns domain-driven service boundaries API/event strategy and reusable platform capabilities.
• Own end-to-end delivery and operations ensuring production readiness incident management reliability/SLOs observability cost governance and continuous improvement.
• Oversee integrations into HR workforce and compensation systems workflow tooling identity/access systems analytics and external SAAS vendors; ensure resilient integration patterns and strong data contracts.
• Establish and enforce engineering governance: secure coding standards architecture review SDLC controls change management audit readiness and measurable engineering KPIs (availability latency defect escape rate lead time cost to serve).
• Partner with Product UX and HR stakeholders to translate strategy into outcomes manage trade-offs and ensure solutions solve real business problems.
• Manage third-party vendor and platform relationships: due diligence technical fit security posture delivery oversight and commercial/operational accountability (in partnership with sourcing and product).
• Champion a strong engineering culture grounded in inclusion accountability high standards and continuous learning; promote responsible use of AI-assisted development with appropriate guardrails.
• Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed quality and operational outcomes (e.g. AI-orchestrated delivery workflows release readiness controls automated test modernization and incident triage acceleration) while establishing guardrails for validation security resiliency traceability and reuse across teams.
• Applies knowledge of tools within the Software Development Life Cycle toolchain including enterprise-authorized AI-assisted development and automation capabilities to improve the value realized by automation and support capacity unlock initiatives at scale.

Required Qualifications Capabilities and Skills

• Formal training or certification on software engineering concepts and expert applied addition experience leading technologists to manage anticipate and solve complex technical items within your domain of expertise.
• Hands-on experience with modern full-stack engineering including React/TypeScript and enterprise design systems.
• Production implementation experience with large scale Graph databases (e.g. Neptune Neo4J TigerGraph).
• Familiarity with industry standard cloud data persistence (e.g. PostgreSQL/Aurora). Strong knowledge of cloud-native engineering (e.g. AWS or equivalent) including reliability security cost management and SDLC automation.
• Backend and API expertise with Java/Spring Boot and strong GraphQL/REST API design versioning and governance practices. Experience delivering modern web and API platforms including distributed systems service-oriented architecture/microservices and integration-heavy domains.
• Solid security and data fundamentals including OAuth2/OIDC service-to-service security patterns
• Proven track record leading mission-critical platforms with high availability strong operational excellence and measurable outcomes.
• Demonstrated ability to influence and align senior business product and technology stakeholders including communicating strategy risks and delivery status with clarity. Alongside experienced people leader: hiring mentoring talent development building inclusive/high-performing teams.
• Hands-on understanding of engineering controls and security: identity/access management data privacy secure SDLC vulnerability management and audit/compliance expectations.
• Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams including defining operating expectations (human-in-the-loop validation quality gates) measuring outcomes and ensuring secure handling of sensitive inputs/outputs.
• Strong understanding of responsible AI use and control expectations in engineering workflows including data sensitivity resiliency/security implications and governance; ability to influence leaders on safe scaling patterns and reuse.

Preferred Qualifications Capabilities and Skills

• Experience with HR technology and Talent performance management workflows.
• Proven ability integrating talent/HR applications with enterprise HR suites (e.g. Oracle HCM or similar) and broader vendor ecosystems.
• Experience with event-driven architectures using Kafka/MSK including schema evolution idempotency patterns and operational controls (e.g. DLQs).
• Strong platform engineering and delivery practices: CI/CD automated testing strategies IaC (Terraform/CloudFormation/CDK) containers (ECS/EKS) plus establishing standards (service blueprints API/event contract governance SLO/SLI frameworks) and responsible AI-assisted engineering practices (secure usage quality gates productivity enablement).